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Algorithmic Trading and Machine Learning
 
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Michael Kearns, University of Pennsylvania Algorithmic Game Theory and Practice https://simons.berkeley.edu/talks/michael-kearns-2015-11-19
Views: 52267 Simons Institute
Machine Learning for Algorithmic Trading | Part 1: Machine Learning & First Steps
 
01:08:03
Discover how to prepare your computer to learn and build a strong foundation for machine learning In this series, quantitative trader Trevor Trinkino will walk you through a step-by-step introductory process for implementing machine learning and how you can turn this into a trading algorithm using Python. Plus he will show you the process of tuning your parameters for better performance of your trading system. For additional resources on algorithmic trading, python, machine learning, API, and more please visit https://www.quantnews.com/resources/ Remember that forex and CFD trading can result in losses that could exceed your deposited funds and therefore may not be suitable for everyone, so please ensure that you fully understand the risks involved. The guest speaker(s) is neither an employee, agent nor representative of FXCM and is therefore acting independently. The opinions given are their own, constitute general market commentary, and do not constitute the opinion or advice of FXCM or any form of personal or investment advice. FXCM neither endorses nor guarantees offerings of third party speakers, nor is FXCM responsible for the content, veracity or opinions of third-party speakers, presenters or participants. Any opinions, news, research, analyses, prices, or other information is provided as general market commentary, and does not constitute investment advice. FXCM will not accept liability for any loss or damage, including without limitation to, any loss of profit, which may arise directly or indirectly from use of or reliance on such information.
Views: 15463 Quant News
Machine learning for algorithmic trading w/ Bert Mouler
 
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EP 042: Harnessing the power of machine learning for money making algo strategies w/ Bert Mouler More interviews: http://chatwithtraders.com Free eBook: http://chatwithtraders.com/17lessons Twitter: https://twitter.com/chatwithtraders Facebook: http://facebook.com/chatwithtraders Instagram: https://instagram.com/chatwithtraders_ Soundcloud: https://soundcloud.com/chat-with-traders Sitcher: http://www.stitcher.com/podcast/chat-...
Views: 58273 Chat With Traders
How A.I. Traders Will Dominate Hedge Fund Industry   | Marshall Chang | TEDxBeaconStreetSalon
 
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We've seen fully automated bot beats us in Go, one-on-one Poker and Dota II, now what's going to happen for trading financial markets? Listen to A.I. Capital Management sharing their research, a Deep Learning trading agent that over-performs us in trading FX markets. Marshall has been trading FX markets for 5 years. As a Master in Finance graduate from Brandeis International Business school, he combines his insight in financial markets with a passion for machine learning and expertise in programming, striving to build the first game-changing A.I. trading system to disrupt the markets. He has a strong passion for quantitative trading and machine learning and started AI Capital Management in September 2016. His inspiration came from Google DeepMind’s AlphaGo project, which is a Deep Learning agent that beats human Go world champions. Go, as a game with complexity at a number more than the atom in the universe, is arguably as hard as or even harder than trading financial markets, which they believe is the next game to be solved with Artificial Intelligence. This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at https://www.ted.com/tedx
Views: 60641 TEDx Talks
Machine Learning and Pattern Recognition for Algorithmic Forex and Stock Trading: Intro
 
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Welcome to the Machine Learning for Forex and Stock analysis and algorithmic trading tutorial series. In this series, you will be taught how to apply machine learning and pattern recognition principles to the field of stocks and forex. The file: http://sentdex.com/GBPUSD.zip This is especially useful for people interested in quantitative analysis and algo trading. Even if you are not, the series will still be of great use to anyone interested in learning about machine learning and automatic pattern recognition, through a hands-on tutorial series. Sentdex.com Facebook.com/sentdex Twitter.com/sentdex
Views: 188172 sentdex
Stock Price Prediction | AI in Finance
 
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Can AI be used in the financial sector? Of course! In fact, finance was one of the pioneering industries that started using AI in the early 80s for market prediction. Since then, major financial firms and hedge funds have adopted AI technologies for everything from portfolio optimization, to credit lending, to stock betting. In this video, we'll go over all the different ways AI can be used in applied finance, then build a stock price prediction algorithm in python using Keras and Tensorflow. Code for this video: https://github.com/llSourcell/AI_in_Finance Please Subscribe! And like. And comment. That's what keeps me going. Want more education? Connect with me here: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology instagram: https://www.instagram.com/sirajraval More learning resources: https://hackernoon.com/unsupervised-machine-learning-for-fun-profit-with-basket-clusters-17a1161e7aa1 https://www.datacamp.com/community/tutorials/finance-python-trading http://www.cuelogic.com/blog/python-in-finance-analytics-artificial-intelligence/ https://www.udacity.com/course/machine-learning-for-trading--ud501 https://www.oreilly.com/learning/algorithmic-trading-in-less-than-100-lines-of-python-code Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ Sign up for the next course at The School of AI: https://www.theschool.ai And please support me on Patreon: https://www.patreon.com/user?u=3191693 Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w Hit the Join button above to sign up to become a member of my channel for access to exclusive content!
Views: 183000 Siraj Raval
Tutorial: Deep Reinforcement Learning For Algorithmic Trading in Python
 
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In this tutorial, we'll see an example of deep reinforcement learning for algorithmic trading using BTGym (OpenAI Gym environment API for backtrader backtesting library) and a DQN algorithm from a medium post (link below) to interact with the environment and does the trading. Access to the code: https://gist.github.com/arsalanaf/d10e0c9e2422dba94c91e478831acb12 Telegram Group: https://t.me/joinchat/DmGkrhIE_g6Mk-zJS6sWgA Links: OpenAI Gym: https://gym.openai.com/ BTGym: https://github.com/Kismuz/btgym backtrader: https://www.backtrader.com/ TensorForce: https://github.com/reinforceio/tensorforce Bitcoin TensorForce Trading Bot: https://github.com/lefnire/tforce_btc_trader Self Learning Quant: https://hackernoon.com/the-self-learning-quant-d3329fcc9915 DQN: https://towardsdatascience.com/reinforcement-learning-w-keras-openai-dqns-1eed3a5338c
Views: 18452 Python for Trading
Algorithmic Trading with Python and Quantopian p. 1
 
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In this tutorial, we're going to begin talking about strategy back-testing. The field of back testing, and the requirements to do it right are pretty massive. Basically, what's required for us is to create a system that will take historical pricing data and simulate trading in that environment, and then gives us the results. https://pythonprogramming.net https://twitter.com/sentdex https://www.facebook.com/pythonprogramming.net/ https://plus.google.com/+sentdex
Views: 152865 sentdex
Practical Tips For Algorithmic Trading (Using Machine Learning)
 
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Evgeny “Jenia” Mozgunov (Caltech) won an algorithmic trading competition hosted by Quantiacs. Jenia used machine learning tools to write his trading algorithm that now trades an initial $1M investment. He is talking about his approach and his main learnings. Jenia's algorithm currently has a live Sharpe Ratio of 2.66.
Views: 31723 Quantiacs
Algorithmic Trading using Machine Learning in Python
 
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AlgoJi is largest community of Algo Traders in India. Check free courses on Amibroker, Python, Excel etc to kickstart algo trading on https://algoji.com/ Use AlgoJi APIBridge for full autotrading with Zerodha, Upstox, Interactive Brokers, Sharekhan etc. It integrates with Amibroker, Excel, Python, MT4 and all popular platforms. Check details here https://algoji.com/apibridge-documentation/
Views: 5850 AlgoJi
Machine Learning for Stock Trading  [Part 1]
 
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Full project with files for FREE here: http://bit.ly/2XeqEXM Part 1: Init/Clone Github Repo; Create a Broker Account Have you ever wondered if AI could earn a tremendous amount of money on the stock market and outsmart other human investors? An AI-powered trading robot can automatically make trade decisions on your behalf and allow you to profit from the market without your direct involvement. In this project tutorial, you’ll learn how to use machine learning to develop a stock trading robot. You’ll gain all the essential skills to create a full-fledged stock trading algorithm that investors and traders can utilize in their trading. In this project, we’ll start by developing an application that reads price data from an API and saves it on a MongoDB database. Another part of this application will be using the saved data for training a machine learning model, optimizing, and then saving it. The last part will be using the saved model and applying it to real-time data provided by the brokerage company while trying to predict the stock price movements. It’s that exciting! What are the requirements? You’ll grasp the concepts described in this project quickly if you have some basic skills in the following: Python 3.5+ Database knowledge (understanding of MongoDB or NoSQL) Mathematical skills Machine learning tools and technologies such as Anaconda, Jupyter, Keras, Scikit-learn, and TensorBoard And the most important is: desire to learn Who is the target audience? Do you want to build an automated trading system? Do you want to learn more about the financial markets? Do you want to learn more about machine learning and neural networks? Do you want to know how AI can be applied to investing? What will you learn after finishing this project? How to create trading robots for executing orders on the stock market automatically How to apply algorithmic trading using probabilistic machine learning techniques How to create an application that accesses live market data, evaluates it, and decides whether to place trades How to optimize a trading robot for profitable trading in the financial markets Full project with files for FREE here: http://bit.ly/2XeqEXM
Views: 2516 Education Ecosystem
"The Machine Learning Approach" by Michael Kearns
 
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by Michael Kearns, Professor of Computer and Information Science, UPenn. From QuantCon NYC 2015. Traditional financial markets have undergone rapid technological change due to increased automation and the introduction of new exchanges and mechanisms. Such changes have brought with them challenging new problems in algorithmic trading, many of which invite a machine learning approach. In this talk, Michael will examine several algorithmic trading problems, focusing on their novel ML aspects, including limiting market impact, dealing with censored data, and incorporating risk considerations. The slides for this presentation can be found at https://www.slideshare.net/Quantopian/algorithmic-trading-and-machine-learning-by-michael-kearns. To learn more about Quantopian, visit us at https://www.quantopian.com. Disclaimer Quantopian provides this presentation to help people write trading algorithms - it is not intended to provide investment advice. More specifically, the material is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory or other services by Quantopian. In addition, the content neither constitutes investment advice nor offers any opinion with respect to the suitability of any security or any specific investment. Quantopian makes no guarantees as to accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances.
Views: 10346 Quantopian
Machine Learning and Pattern Recognition for Algorithmic Trading p. 17
 
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This video discusses some of the performance issues with the program. Welcome to the Machine Learning for Forex and Stock analysis and automated trading tutorial series. In this series, you will be taught how to apply machine learning and pattern recognition principles to the field of stocks and forex. This is especially useful for people interested in quantitative analysis and algo or high frequency trading. Even if you are not, the series will still be of great use to anyone interested in learning about machine learning and automatic pattern recognition, through a hands-on tutorial series. Sentdex.com Facebook.com/sentdex Twitter.com/sentdex
Views: 9843 sentdex
Crypto Trading With Neural Networks: Machine Learning & Markets
 
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Resources from this video: Brain.js: https://github.com/BrainJS/brain.js ViewEx: https://www.viewex.io Avocado Signup: https://avocado.proofsuite.com You can reach us at [email protected]
Views: 6247 Proof Suite
Machine Learning For Traders: Technical Indicators - Part 1
 
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In the previous video of this series (https://youtu.be/0IWLfTomLLg) we learnt about the different types of classifier algorithms. In this video, we will discuss the following Technical Indicators: - Relative Strength Index (RSI) - Definition - Formula - Use in trading - Simple Moving Average (SMA) - Definition - Formula - Use in trading - Correlation Coefficient - Definition - Formula - Use in trading f you want to master the whole course: Trading With Machine Learning: Classification and SVM. Head on over to the following link: https://quantra.quantinsti.com/course/trading-machine-learning-classification-svm If you want to learn more about machine learning for free, check out the following link: https://quantra.quantinsti.com/course/introduction-to-machine-learning-for-trading QuantInsti® is one of the pioneer algorithmic trading research and training institutes across the globe. With its educational initiatives, QuantInsti is preparing financial market professionals for the contemporary field of algorithmic and quantitative trading. EPAT™ (Executive Programme in Algorithmic Trading) by QuantInsti is Asia’s first algorithmic trading education program. This comprehensive course exposes its participants to various strategy paradigms and enables them to build an algorithmic trading system. Quantra® is an e-learning portal by QuantInsti that specializes in short self-paced courses on algorithmic and quantitative trading. Quantra offers an interactive environment which supports ‘learning by doing’ through guided coding exercises, videos and presentations.
Python for Algorithmic Trading | The AI Machine
 
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This is the recording of the QUANTACT Webinar by Dr Yves Hilpisch (The Python Quants | The AI Machine) from 07 Feb 2019. Link to the slides: https://certificate.tpq.io/qaweb.pdf Link to the notebook: https://certificate.tpq.io/qaweb.html
Views: 2253 Yves Hilpisch
TEDxNewWallStreet - Sean Gourley - High frequency trading and the new algorithmic ecosystem
 
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Speaker Bio: Dr. Sean Gourley is the founder and CTO of Quid. He is a Physicist by training and has studied the mathematical patterns of war and terrorism. He is building tools to augment human intelligence. Description of Talk: The speed of human strategic thinking is fundamentally limited by the biological hardware that makes up the brain. As humans we simply cannot operate on the millisecond time scale -- but algorithms can, and it is these algorithms that are now dominating the financial landscape. In this talk Sean Gourley examines this high frequency algorithmic ecosystem. An ecosystem, Gourley argues, that has evolved to the point where we as humans are no longer fully in control. About TEDx: In the spirit of ideas worth spreading, TEDx is a program of local, self-organized events that bring people together to share a TED-like experience. At a TEDx event, TEDTalks video and live speakers combine to spark deep discussion and connection in a small group. These local, self-organized events are branded TEDx, where x = independently organized TED event. The TED Conference provides general guidance for the TEDx program, but individual TEDx events are self-organized.* (*Subject to certain rules and regulations)
Views: 318751 TEDx Talks
Machine Learning for Algorithmic Trading | Part 2 Preparing Data and Training
 
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In Part 2, you will learn how to select the most important features to extract and clean your data. In this series, quantitative trader Trevor Trinkino will walk you through a step-by-step introductory process for implementing machine learning and how you can turn this into a trading algorithm using Python. Plus he will show you the process of tuning your parameters for better performance of your trading system. For additional resources on algorithmic trading, python, machine learning, API, and more please visit https://www.quantnews.com/resources/ Remember that forex and CFD trading can result in losses that could exceed your deposited funds and therefore may not be suitable for everyone, so please ensure that you fully understand the risks involved. The guest speaker(s) is neither an employee, agent nor representative of FXCM and is therefore acting independently. The opinions given are their own, constitute general market commentary, and do not constitute the opinion or advice of FXCM or any form of personal or investment advice. FXCM neither endorses nor guarantees offerings of third party speakers, nor is FXCM responsible for the content, veracity or opinions of third-party speakers, presenters or participants. Any opinions, news, research, analyses, prices, or other information is provided as general market commentary, and does not constitute investment advice. FXCM will not accept liability for any loss or damage, including without limitation to, any loss of profit, which may arise directly or indirectly from use of or reliance on such information.
Views: 4061 Quant News
Leveraging Artificial Intelligence to Build Algorithmic Trading Strategies
 
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Our guest speaker, Mr. Tad Slaff, CEO of Inovance had covered the following content in a 45-mins long presentation: 1. Strategy Development Applications - Indicator Selection - Pattern Recognition Algorithms - Association Rule Learning 2. Building a live strategy with TRAIDE It was a well-received webinar with attendees learning how to include machine learning algorithms in a live trading strategy. You can view webinar presentation slides at http://www.slideshare.net/QuantInsti/leveraging-artificial-intelligence-to-build-algorithmic-trading-strategies Additional Resources for Machine Learning: - http://www.quantinsti.com/blog/free-resources-learn-machine-learning-trading/ - https://www.youtube.com/watch?v=EXtyBHTplCs Finally, check out the QuantInsti’s Executive Program in Algorithmic Trading at www.quantinsti.com/courses/epat. You will find the course covers comprehensive trading in Algorithmic Trading, taught by some of the experts in this field. On our Youtube channel and blogs, get strategy ideas and downloadable models to get started trading immediately! If you would like more information about QuantInsti’s offerings, please write to us at [email protected] Most Useful links Join EPAT – Executive Programme in Algorithmic Trading : https://goo.gl/3Oyf2B Visit us at: https://www.quantinsti.com/ Like us on Facebook: https://www.facebook.com/quantinsti/ Follow us on Twitter: https://twitter.com/QuantInsti
Machine Learning in High Frequency Trading - qplum FinTech Talks
 
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This Fin-tech talk by qplum co-founder Gaurav Chakravorty is about how a bunch of data scientists brought about disruption in two huge and well-protected business lines using machine learning + systems + APIs. What is the real business of HFT today and how did it start? Where does ML really help in HFT. In this talk, Gaurav also works through an example of how people in quant-trading improved upon their initial work. Disclaimer: The views and opinions expressed in this video are purely those of the speaker and are not reflective of qplum. Investment strategies, results and any other information presented are for education and research purposes only. All investments carry risk and backtested performances are not indicative of future performances. Please visit our website qplum.co for terms of use.
Views: 10732 qplum
Data Structures and Algorithmic Trading: Machine Learning : Greedy Algorithms
 
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http://ytwizard.com/r/BfMhXF http://ytwizard.com/r/BfMhXF Data Structures and Algorithmic Trading: Machine Learning Data Structures and Algorithmic Trading: Machine Learning, Stock Trading, Invest In Cryptocurrency, Build A Forex Robot
Views: 47 All in one
Machine Learning For Traders: An Introduction
 
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In this short video, we will go through the following points: - What is Machine Learning? - The difference between a regular and a machine learning algorithm - Examples of Machine Learning (ML) algorithms in the real world. (Did you know Facebook uses ML algorithms to match different pictures of the same person and identify them) - Industries using machine learning - Implementation and usage of machine learning in trading - Advantages of a trader using machine learning over a regular trader The full course is available on the following link: https://quantra.quantinsti.com/course/introduction-to-machine-learning-for-trading And guess what, it is FREE. QuantInsti® is one of the pioneer algorithmic trading research and training institutes across the globe. With its educational initiatives, QuantInsti is preparing financial market professionals for the contemporary field of algorithmic and quantitative trading. EPAT™ (Executive Programme in Algorithmic Trading) by QuantInsti is Asia’s first algorithmic trading education program. This comprehensive course exposes its participants to various strategy paradigms and enables them to build an algorithmic trading system. Quantra® is an e-learning portal by QuantInsti that specializes in short self-paced courses on algorithmic and quantitative trading. Quantra offers an interactive environment which supports ‘learning by doing’ through guided coding exercises, videos and presentations.
Aishwarya Srinivasan - High Frequency Trading using deep learning - AI With The Best Oct 2017
 
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AI With The Best hosted 50+ speakers and hundreds of attendees from all over the world on a single platform on October 14-15, 2017. The platform held live talks, Insights/Questions pages, and bookings for 1-on-1s with speakers. In the talk, emphasis will be made on the proposed deep learning strategies applied to design algorithm for the implementation of High Frequency Trading. The deep learning concept applied was achieved by training the neural network with the current date, hour and minute, time series analysis, standard deviations an predictor indicator for predicting the next minute's stock price. It is seen that the stock prices prediction cannot be made just based on the trend analytics, the prices may vary because of other parameters of the market as well. In order to have a more precise analysis, market situation needs to be understood. For the purpose, text analysis of the Twitter data is done. The prediction model for the HFT involves both quantitative data of the previous minutes' data as well as quantitative data from Twitter. The analysis is done on the Amazon.com Inc (AMZN) data, from March 2017 to August 2017; the prices seem to have a constant increase since March. Soon after the acquisition of Whole Foods during June second week, the Amazon's stock market hit a high of 1082.65 on July 27, 2017; which made Jeff Bezos the richest man in the world with Amazon's stake hit the high of $86.5bn. The research is the first of its kind to take into consideration both qualitative and quantitative data for stock prediction. http://withthebest.com/ https://twitter.com/WithTheBest https://www.facebook.com/WithTheBestConf
Views: 1303 With The Best
Conclusion - Machine Learning and Pattern Recognition for Algorithmic Trading p. 19
 
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In this video, the series is wrapped up. Welcome to the Machine Learning for Forex and Stock analysis and algorithmic trading tutorial series. In this series, you will be taught how to apply machine learning and pattern recognition principles to the field of stocks and Forex. This is especially useful for people interested in quantitative analysis and algo or high frequency trading. Even if you are not, the series will still be of great use to anyone interested in learning about machine learning and automatic pattern recognition, through a hands-on tutorial series. Sentdex.com Facebook.com/sentdex Twitter.com/sentdex
Views: 20647 sentdex
Pattern Recognition: Machine Learning for Algorithmic Trading Part 9
 
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Welcome to the Machine Learning for Forex and Stock analysis and algorithmic trading tutorial series. In this series, you will be taught how to apply machine learning and pattern recognition principles to the field of stocks and forex. This is especially useful for people interested in quantitative analysis and algo or high frequency trading. Even if you are not, the series will still be of great use to anyone interested in learning about machine learning and automatic pattern recognition, through a hands-on tutorial series. Sentdex.com Facebook.com/sentdex Twitter.com/sentdex
Views: 14242 sentdex
Machine Learning for Quantitative Trading Webinar with Dr. Ernie Chan
 
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Quantitative trading and algorithmic trading expert Dr. Ernie Chan teaches you machine learning in quantitative finance. You will learn: 1) The pros and cons of applying machine learning to trading and investing. 2) What are the best types of data for ML algorithms? 3) What are the ML algorithms most useful to traders and investors? 4) Can the machine really replace humans in trading?
Views: 14976 Quantiacs
Machine Learning For Traders - An Introduction To Classification
 
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In the previous video of this series (https://youtu.be/oG4ks-9zYn8) we learnt how to import Python libraries. In this video, we will discuss the following points: - Introduction to Classification - Application in various fields such as: - Medical Diagnosis - Fraud detection - Handwriting recognition - Customer segmentation - Risk assessment - An example of a Classification used by E-Commerce websites - It is not restricted to text and numbers, even images can be classified. - Supervised classifier algorithms - The classifier algorithms can be chosen, depending on - Size of training data - Independence of features set - System speed The classifier algorithms covered are: - K-Nearest Neighbours Algorithm (KNN) - Random Forests Using Decision Trees - Artificial Neural Networks (ANN) - Naive Bayes Classification If you want to master the whole course: Trading With Machine Learning: Classification and SVM. Head on over to the following link: https://quantra.quantinsti.com/course/trading-machine-learning-classification-svm If you want to learn more about machine learning for free, check out the following link: https://quantra.quantinsti.com/course/introduction-to-machine-learning-for-trading QuantInsti® is one of the pioneer algorithmic trading research and training institutes across the globe. With its educational initiatives, QuantInsti is preparing financial market professionals for the contemporary field of algorithmic and quantitative trading. EPAT™ (Executive Programme in Algorithmic Trading) by QuantInsti is Asia’s first algorithmic trading education program. This comprehensive course exposes its participants to various strategy paradigms and enables them to build an algorithmic trading system. Quantra® is an e-learning portal by QuantInsti that specializes in short self-paced courses on algorithmic and quantitative trading. Quantra offers an interactive environment which supports ‘learning by doing’ through guided coding exercises, videos and presentations.
Pattern Recognition and Outcome: Machine Learning for Algorithmic Trading in Forex and Stocks
 
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Here, we are beginning to compile the past historical patterns that we are comparing to, and taking their eventual outcome for use in future predictions. Welcome to the Machine Learning for Forex and Stock analysis and algorithmic trading tutorial series. In this series, you will be taught how to apply machine learning and pattern recognition principles to the field of stocks and forex. This is especially useful for people interested in quantitative analysis and algo or high frequency trading. Even if you are not, the series will still be of great use to anyone interested in learning about machine learning and automatic pattern recognition, through a hands-on tutorial series. Sentdex.com Facebook.com/sentdex Twitter.com/sentdex
Views: 12244 sentdex
Machine learning algo trading plans for 2019
 
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I cover all popular machine learning frameworks are going mainstream. I am anticipating that Tensor Flow will be the dominant player because of Google. I also talk about the future vision of integrating Redis and Motive Wave trading platform aswell. Other programming languages other Python were covered including C++ and Java https://quantlabs.net/blog/2019/01/machine-learning-algo-trading-plans-2019/
Views: 197 Bryan Downing
“What To Do Before Machine Learning” with Dr. Ernie Chan
 
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“What To Do Before Machine Learning” There is a great temptation to just let a deep neural net loose on your financial data and let it spit out returns predictions. This webinar will show you how to resist that temptation. Ernie Chan will discuss steps such as coming up with the simplest baseline models that financial machine learners often impatiently omit in their workflow. About the Speaker: Dr. Ernest Chan is the Managing Member of QTS Capital Management, LLC., a commodity pool operator and trading advisor. He began his career as a machine learning researcher at IBM’s Human Language Technologies Group, and later joined Morgan Stanley’s Data Mining Group. He was also a quantitative researcher and proprietary trader for Credit Suisse. Ernie is the author of “Machine Trading”, “Algorithmic Trading”, and “Quantitative Trading”, all published by Wiley, and a popular financial blogger at epchan.blogspot.com. He also teaches at the Master of Science in Predictive Analytics program at Northwestern University. He received his Ph.D. in theoretical physics from Cornell University. Disclaimer Quantopian provides this presentation to help people write trading algorithms - it is not intended to provide investment advice. More specifically, the material is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory or other services by Quantopian. In addition, the content neither constitutes investment advice nor offers any opinion with respect to the suitability of any security or any specific investment. Quantopian makes no guarantees as to accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances.
Views: 4362 Quantopian
Variables in Pattern Recognition: Machine Learning for Algorithmic Trading in Forex and Stocks p. 13
 
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This video discusses the already many variables that need to be considered in our pattern recognition and how we use it. Welcome to the Machine Learning for Forex and Stock analysis and algorithmic trading tutorial series. In this series, you will be taught how to apply machine learning and pattern recognition principles to the field of stocks and forex. This is especially useful for people interested in quantitative analysis and algo or high frequency trading. Even if you are not, the series will still be of great use to anyone interested in learning about machine learning and automatic pattern recognition, through a hands-on tutorial series. Sentdex.com Facebook.com/sentdex Twitter.com/sentdex
Views: 9894 sentdex
Algo trader using automation to bypass human flaws · Bert Mouler
 
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EP 142: Using creative thought and automation to bypass human flaws w/ Bert Mouler It was exactly 100-episodes ago when I first had Bert Mouler on the podcast. This week, I’m joined by him again for a second interview… Bert is an algorithmic trader with a serious focus on machine learning. His trading decisions are driven purely by data, and he goes to great lengths to remove human bias and flaws through the use of automation. While listening, I encourage you to keep an open mind and mull over Bert’s creative thoughts. Then if you have any questions afterwards, you’re welcome to post in the comments area at chatwithtraders.com/142.
Views: 10502 Chat With Traders
Machine Learning for Algorithmic Trading | Part 3: Hyper Parameter Tuning
 
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In this series, quantitative trader Trevor Trinkino will walk you through a step-by-step introductory process for implementing machine learning and how you can turn this into a trading algorithm using Python. Plus he will show you the process of tuning your parameters for better performance of your trading system. For additional resources on algorithmic trading, python, machine learning, API, and more please visit https://www.quantnews.com/resources/ Remember that forex and CFD trading can result in losses that could exceed your deposited funds and therefore may not be suitable for everyone, so please ensure that you fully understand the risks involved. The guest speaker(s) is neither an employee, agent nor representative of FXCM and is therefore acting independently. The opinions given are their own, constitute general market commentary, and do not constitute the opinion or advice of FXCM or any form of personal or investment advice. FXCM neither endorses nor guarantees offerings of third party speakers, nor is FXCM responsible for the content, veracity or opinions of third-party speakers, presenters or participants. Any opinions, news, research, analyses, prices, or other information is provided as general market commentary, and does not constitute investment advice. FXCM will not accept liability for any loss or damage, including without limitation to, any loss of profit, which may arise directly or indirectly from use of or reliance on such information.
Views: 2507 Quant News
Current Pattern: Machine Learning for Algorithmic Trading in Forex and Stocks
 
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In this video, we are are locating the latest pattern, in order to compare it to the previous ones for pattern recognition. Welcome to the Machine Learning for Forex and Stock analysis and algorithmic trading tutorial series. In this series, you will be taught how to apply machine learning and pattern recognition principles to the field of stocks and forex. This is especially useful for people interested in quantitative analysis and algo or high frequency trading. Even if you are not, the series will still be of great use to anyone interested in learning about machine learning and automatic pattern recognition, through a hands-on tutorial series. Sentdex.com Facebook.com/sentdex Twitter.com/sentdex
Views: 19360 sentdex
Pattern Finding and Storing: Machine Learning for Algorithmic Trading in Forex and Stocks Part 6
 
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In this video, we are finding and storing patterns to be later used in the pattern recognition. Welcome to the Machine Learning for Forex and Stock analysis and algorithmic trading tutorial series. In this series, you will be taught how to apply machine learning and pattern recognition principles to the field of stocks and forex. This is especially useful for people interested in quantitative analysis and algo or high frequency trading. Even if you are not, the series will still be of great use to anyone interested in learning about machine learning and automatic pattern recognition, through a hands-on tutorial series. Sentdex.com Facebook.com/sentdex Twitter.com/sentdex
Views: 25304 sentdex
FinBrain Technologies - Deep Learning Algorithmic Trading Bot
 
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FinBrain Technologies - https://finbrain.tech is a FinTech company, which develops Deep Learning algorithms to provide our customers with the most precise future predictions of Stocks, Commodities, Foreign Currencies, Indexes and ETFs. FinBrain Technologies Past Performances Blog - https://finbrain.tech/blog Our algorithm uses sophisticated deep learning/artificial neural network approach for time series analysis. Time series data is processed using self-adapting and self-optimizing algorithms, and is fed into the Neural Network. The network is then trained, and the multi-day ahead predictions are generated. FinBrain’s algorithm is a combination of different Mathematical and Deep Learning approaches, which analyzes the characteristics of time-series data for any Stock, Commodity, Foreign Currency, Index and ETF.
Views: 2184 FinBrain Technologies
#TechSpotlight: How Machine Learning is Transforming Trading Strategies | J.P. Morgan
 
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SUBSCRIBE: http://jpm.com/x/i/NFPWfK0 J.P. Morgan's Global Head of Equities Electronic Trading shares insights on the opportunities that machine learning creates for the industry. About J.P. Morgan: J.P. Morgan is a leader in financial services, offering solutions to clients in more than 100 countries with one of the most comprehensive global product platforms available. We have been helping our clients to do business and manage their wealth for more than 200 years. Our business has been built upon our core principle of putting our clients' interests first. Connect with J.P. Morgan Online: Visit the J.P. Morgan Website: https://www.jpmorgan.com/ Follow @jpmorgan on Twitter: https://twitter.com/jpmorgan Visit our J.P. Morgan Facebook page: http://facebook.com/jpmorgan Follow J.P. Morgan on LinkedIn: https://linkedin.com/company/j-p-morgan/ Follow @jpmorgan on Instagram: https://instagram.com/jpmorgan/ #jpmorgan #TechSpotlight: How Machine Learning is Transforming Trading Strategies | J.P. Morgan
Views: 45944 jpmorgan
Q Learning for Trading
 
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We can use reinforcement learning to build an automated trading bot in a few lines of Python code! In this video, i'll demonstrate how a popular reinforcement learning technique called "Q learning" allows an agent to approximate prices for stocks in a portfolio. The literature of reinforcement learning is incredibly rich. There are so many concepts, like TD-Learning and Actor-Critic for example, that have real-world potential. I hope this video gives you insight into how this incredibly powerful yet simple algorithm works, enjoy! Code for this video: https://github.com/llSourcell/Q-Learning-for-Trading Please Subscribe! And like. And comment. That's what keeps me going. Want more education? Connect with me here: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology instagram: https://www.instagram.com/sirajraval The School of AI: https://www.theschool.ai Github Syllabus: https://github.com/llSourcell/Move_37_Syllabus More learning resources: http://www.wildml.com/2018/02/introduction-to-learning-to-trade-with-reinforcement-learning/ http://cs229.stanford.edu/proj2009/LvDuZhai.pdf https://medium.com/@gaurav1086/machine-learning-for-algorithmic-trading-f79201c8bac6 https://github.com/edwardhdlu/q-trader http://www1.mate.polimi.it/~forma/Didattica/ProgettiPacs/BrambillaNecchi15-16/PACS_Report_Pierpaolo_Necchi.pdf Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ And please support me on Patreon: https://www.patreon.com/user?u=3191693 #QLearningForTrading #SirajRaval Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w Hiring? Need a Job? See our job board!: www.theschool.ai/jobs/ Need help on a project? See our consulting group: www.theschool.ai/consulting-group/ Hit the Join button above to sign up to become a member of my channel for access to exclusive content!
Views: 37191 Siraj Raval
Algo Trading | Introduction to Machine Learning with CloudQuant
 
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Watch this webinar for an introduction to machine learning. Learn about the basic terminology of machine learning and how to give your algorithmic trading strategy the ability to learn from data. For additional resources on algorithmic trading, python, machine learning, API, and more please visit https://www.quantnews.com/resources/ Remember that forex and CFD trading can result in losses that could exceed your deposited funds and therefore may not be suitable for everyone, so please ensure that you fully understand the risks involved. The guest speaker(s) is neither an employee, agent nor representative of FXCM and is therefore acting independently. The opinions given are their own, constitute general market commentary, and do not constitute the opinion or advice of FXCM or any form of personal or investment advice. FXCM neither endorses nor guarantees offerings of third party speakers, nor is FXCM responsible for the content, veracity or opinions of third-party speakers, presenters or participants. Any opinions, news, research, analyses, prices, or other information is provided as general market commentary, and does not constitute investment advice. FXCM will not accept liability for any loss or damage, including without limitation to, any loss of profit, which may arise directly or indirectly from use of or reliance on such information.
Views: 2024 Quant News
Bitcoin Trading Bot (Tutorial)
 
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Cryptocurrency can be a high-risk, high-reward game for those willing to deal with the volatility. Can we use AI to help us make predictions about Bitcoin's future price? In this video, i'll show you how to build a simple Bitcoin trading bot using an LSTM neural network in Keras. Along the way I'll explain why we use LSTM networks through code and animations, as well as a review of the vanishing gradient problem. Code for this video: https://github.com/llSourcell/Bitcoin_Trading_Bot Please Subscribe! And like. And comment. That's what keeps me going. Want more education? Connect with me here: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology instagram: https://www.instagram.com/sirajraval This video is apart of my Machine Learning Journey course: https://github.com/llSourcell/Machine_Learning_Journey More Learning Resources: https://medium.com/swlh/developing-bitcoin-algorithmic-trading-strategies-bfdde5d5f6e0 https://bitcoin.stackexchange.com/questions/48093/how-to-build-a-bitcoin-trading-bot https://blog.patricktriest.com/analyzing-cryptocurrencies-python/ https://github.com/lefnire/tforce_btc_trader Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ Sign up for the next course at The School of AI: https://www.theschool.ai And please support me on Patreon: https://www.patreon.com/user?u=3191693 Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w Hit the Join button above to sign up to become a member of my channel for access to exclusive content!
Views: 38864 Siraj Raval
Increasing Pattern Complexity: Machine Learning for Algorithmic Trading in Forex and Stocks
 
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In this tutorial, we increase the pattern complexity, ie: increase the pattern length for pattern recognition. Welcome to the Machine Learning for Forex and Stock analysis and algorithmic trading tutorial series. In this series, you will be taught how to apply machine learning and pattern recognition principles to the field of stocks and forex. This is especially useful for people interested in quantitative analysis and algo or high frequency trading. Even if you are not, the series will still be of great use to anyone interested in learning about machine learning and automatic pattern recognition, through a hands-on tutorial series. Sentdex.com Facebook.com/sentdex Twitter.com/sentdex
Views: 13286 sentdex
Machine Learning framework for Algorithmic trading on Energy markets
 
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Machine Learning framework for Algorithmic trading on Energy markets I add my view of this article within this video http://quantlabs.net/blog/2018/07/autograph-converts-python-tensorflow-graphs-ml-model-add-view-article-within-video/
Views: 271 Bryan Downing
Reinforcement Learning for Trading - Practical Examples and Lessons Learned | Dr Tom Starke
 
01:12:48
Over the last two decades trading has seen a remarkable evolution from open-outcry in the Wall Street pits to screen trading all the way to current automation and high-frequency trading (HFT). The success of machine learning and artificial intelligence (AI) seems like natural progression for the evolution of trading. In this talk, Dr. Tom Starke presents a glimpse of the applications of machine learning in autonomous trading systems and provides some practical examples where reinforcement learning is used for devising trading strategies. About the Speaker: Dr. Tom Starke(CEO, AAA Quants) has a PhD. in Physics and is tremendously interested in Mathematical modeling and machine learning in Financial markets. He has previously lectured computer simulation at Oxford University and lead strategic research projects for Rolls-Royce Plc. Check out more TechJam talks https://techjam.org/ TechJam is a non-profit initiative to build a community of techies, who are interested in learning and exploring new technologies. Follow TechJam on Twitter: https://twitter.com/TechJam_In Like TechJam on Facebook: https://www.facebook.com/techjam.pune
Views: 1126 TechJam
Average prediction pattern recognition Machine Learning for Algorithmic Trading
 
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Using previous pattern outcomes to help us begin to predict future outcomes. Welcome to the Machine Learning for Forex and Stock analysis and automated trading tutorial series. In this series, you will be taught how to apply machine learning and pattern recognition principles to the field of stocks and forex. This is especially useful for people interested in quantitative analysis and algo or high frequency trading. Even if you are not, the series will still be of great use to anyone interested in learning about machine learning and automatic pattern recognition, through a hands-on tutorial series. Sentdex.com Facebook.com/sentdex Twitter.com/sentdex
Views: 10895 sentdex
"A Guided Tour Of Machine Learning For Traders" by Dr. Tucker Balch
 
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by Dr. Tucker Balch, Chief Scientist at Lucena Research, Professor at Georgia Tech. From QuantCon NYC 2016. You’ve probably heard about Machine Learning and you likely know it is of emerging importance for trading and investing. Unfortunately it is a deeply technical field and the complexity and jargon get in the way of broader use and understanding. There are literally hundreds of learning algorithms that each solve a slightly different problem. Which algorithms really matter for investing? In this presentation, Professor Balch will help declutter the ML jungle. He’ll introduce a few of the most important ML algorithms and show how they can be applied to the challenges of trading. The slides for this presentation can be found at https://www.slideshare.net/Quantopian/a-guided-tour-of-machine-learning-for-traders-by-tucker-balch-at-quantcon-2016. To learn more about Quantopian, visit us at https://www.quantopian.com. Disclaimer Quantopian provides this presentation to help people write trading algorithms - it is not intended to provide investment advice. More specifically, the material is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory or other services by Quantopian. In addition, the content neither constitutes investment advice nor offers any opinion with respect to the suitability of any security or any specific investment. Quantopian makes no guarantees as to accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances.
Views: 13656 Quantopian
Displaying all Patterns Recognized: Machine Learning for Algorithmic Trading in Forex and Stocks
 
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In this video, you are shown how to display all of the patterns at the same time, to make comparing visually easier. Plus it makes for pretty pictures...for all you graph and data lovers out there. Welcome to the Machine Learning for Forex and Stock analysis and algorithmic trading tutorial series. In this series, you will be taught how to apply machine learning and pattern recognition principles to the field of stocks and forex. This is especially useful for people interested in quantitative analysis and algo or high frequency trading. Even if you are not, the series will still be of great use to anyone interested in learning about machine learning and automatic pattern recognition, through a hands-on tutorial series. Sentdex.com Facebook.com/sentdex Twitter.com/sentdex
Views: 13384 sentdex
Cryptocurrency Price Prediction: Machine Learning Trading Algorithm (XGBOOST)
 
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ARTIST CREDIT Evgeny Rodygin - https://www.artstation.com/erodygin ----------------------------------------------- If you want to utlilise the power of machine learning to predict price in cryptocurrency you need to be paying attention to the right things. Today we’ll be looking at the XGBOOST algorithm and how it has been applied in other industries and also how you can use it in the crypto space. You’ll see here the link to data and machine learning is fundamental to the bigger picture. Understand the opportunity in this space and how you can use this to your advantage. #cryptocurrency #machinelearning #cryptoalgorithm ABOUT CRYPTO WIZARDS ----------------------------------------------- Hey there - thanks for stopping by! We are Crypto Wizards! We help a range of people from crypto newbies to aspiring data junkies to make money in ways others have missed. We access cryptocurrency arbitrage opportunities, tools, and machine learning data that we share exclusively with our limited members. Our belief is that change is happening right now in the marketplace. If you are willing to learn and develop your own trading tools, you’ll have a unique advantage. ►Check out our website here: https://cryptowizards.net/ ► Start your Machine Learning & Trading journey: https://cryptowizards.net/contact/ ------------------------------------ ENGAGE WITH US ------------------------------------ Thanks for taking the time to watch this video! We hope that it gave you a behind-the-scenes insight into the world of cryptocurrency! If you found it useful - hit the like button and share it with a friend. Also, leave us a comment with any questions, feedback or thoughts and we’ll get right back to you! Don’t forget to subscribe to this channel to learn more about cryptocurrency, trading and investing. ►https://www.youtube.com/channel/UCRQAKYTbd0H0gH_07bNmPBA/featured?sub_confirmation=1
Views: 363 Crypto Wizards
Preparing back-test: Machine Learning and Pattern Recognition for Algorithmic Trading p. 18
 
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In this video, we set up the back-testing for our pattern recognition and predictions. Welcome to the Machine Learning for Forex and Stock analysis and algorithmic trading tutorial series. In this series, you will be taught how to apply machine learning and pattern recognition principles to the field of stocks and Forex. This is especially useful for people interested in quantitative analysis and algo or high frequency trading. Even if you are not, the series will still be of great use to anyone interested in learning about machine learning and automatic pattern recognition, through a hands-on tutorial series. Sentdex.com Facebook.com/sentdex Twitter.com/sentdex
Views: 12953 sentdex
The Best Session Machine Learning for Trading by Hrishabh Sanghvi
 
01:13:44
AlgoJi is largest community of Algo Traders in India. Check free courses on Amibroker, Python, Excel etc to kickstart algo trading on https://algoji.com/ Use AlgoJi APIBridge for full autotrading with Zerodha, Upstox, Interactive Brokers, Sharekhan etc. It integrates with Amibroker, Excel, Python, MT4 and all popular platforms. Check details here https://algoji.com/apibridge-documentation/
Views: 1486 AlgoJi
High Frequency Trading | When Machines Take Over Markets | R L Shankar | TEDxGLIMChennai
 
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#HighFrequencyTrading | Know More about our analytics courses: http://bit.ly/2ka1nw8 RL Shankar, Professor of Finance and Analytics at Great Lakes Institute of Management, talks about algorithmic trading, its working and how it dominates the trading market. Shankar also talks about the working of High-Frequency Trading or HFT and its volatility. #TEDx #TEDTalks #GreatLakes Dr R L Shankar is a full-time Professor of Finance and Analytics at Great Lakes Institute of Management. He offers Masters and Doctoral courses on Risk management, Financial derivatives, Algorithmic Trading, Fixed income and credit markets, Financial Risk Analytics, Financial engineering, Financial modelling etc. He is also a visiting faculty at IIMs such as IIM Kozhikode, IIM Trichy, and IIM Ranchi. Shankar has rich experience in offering customized programs for working executives. -------------------------------------------------------------------------------------- PG Program in Business Analytics (PGP-BABI): 12-month program with classroom training on weekends + online learning covering analytics tools and techniques and their application in business. PG Program in Big Data Analytics (PGP-BDA): 12-month program with classroom training on weekends + online learning covering big data analytics tools and techniques, machine learning with hands-on exposure to big data tools such as Hadoop, Python, Spark, Pig etc. PGP-Data Science & Engineering: 6-month weekend and classroom program allowing participants enables participants in learning conceptual building of techniques and foundations required for analytics roles. PG Program in Cloud Computing: 6-month online program in Cloud Computing & Architecture for technology professionals who want their careers to be cloud-ready. Business Analytics Certificate Program (BACP): 6-month online data analytics certification enabling participants to gain in-depth and hands-on knowledge of analytical concepts. About Great Learning: - Great Learning is an online and hybrid learning company that offers high-quality, impactful, and industry-relevant programs to working professionals like you. These programs help you master data-driven decision-making regardless of the sector or function you work in and accelerate your career in high growth areas like Data Science, Big Data Analytics, Machine Learning, Artificial Intelligence & more. - Watch the video to know ''Why is there so much hype around 'Artificial Intelligence'?'' https://www.youtube.com/watch?v=VcxpBYAAnGM - What is Machine Learning & its Applications? https://www.youtube.com/watch?v=NsoHx0AJs-U - Do you know what the three pillars of Data Science? Here explaining all about the pillars of Data Science: https://www.youtube.com/watch?v=xtI2Qa4v670 - Want to know more about the careers in Data Science & Engineering? Watch this video: https://www.youtube.com/watch?v=0Ue_plL55jU - For more interesting tutorials, don't forget to Subscribe our channel: https://www.youtube.com/user/beaconelearning?sub_confirmation=1 - Learn More at: https://www.greatlearning.in/ For more updates on courses and tips follow us on: - Google Plus: https://plus.google.com/u/0/108438615307549697541 - Facebook: https://www.facebook.com/GreatLearningOfficial/ - LinkedIn: https://www.linkedin.com/company/great-learning/ - Follow our Blog: https://www.greatlearning.in/blog/?utm_source=Youtube Great Learning has collaborated with the University of Texas at Austin for the PG Program in Artificial Intelligence and Machine Learning and with UT Austin McCombs School of Business for the PG Program in Analytics and Business Intelligence.
Views: 2132 Great Learning