In the final course from the Machine Learning for Trading specialization, you will be introduced to reinforcement learning (RL) and the benefits of using reinforcement learning in trading strategies. You will learn how RL has been integrated with neural networks and review LSTMs and how they can be applied to time series data. By the end of the course, you will be able to build trading strategies using reinforcement learning, differentiate between actor-based policies and value-based policies, and incorporate RL into a momentum trading strategy.
Reinforcement Learning for Trading Strategies
Reinforcement Learning for Trading Strategies
This course is part of Machine Learning for Trading Specialization
Instructor: Jack Farmer
18,431 already enrolled
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3.5
(233 reviews)
Intermediate level
Recommended experience
12 hours to complete
3 weeks at 4 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Understand the structure and techniques used in reinforcement learning (RL) strategies.
Understand the benefits of using RL vs. other learning methods.
Describe the steps required to develop and test an RL trading strategy.
Describe the methods used to optimize an RL trading strategy.
Skills you'll gain
Details to know
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Taught in English
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This course is part of the Machine Learning for Trading Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 3 modules in this course
In this module, reinforcement learning is introduced at a high level. The history and evolution of reinforcement learning is presented, including key concepts like value and policy iteration. Also, the benefits and examples of using reinforcement learning in trading strategies is described. We also introduce LSTM and AutoML as additional tools in your toolkit to use in implementing trading strategies.
What's included
10 videos1 reading1 app item
In the previous module, reinforcement learning was discussed before neural networks were introduced. In this module, we look at how reinforcement learning has been integrated with neural networks. We also look at LSTMs and how they can be applied to time series data.
What's included
9 videos2 app items
In this module we discuss the practical steps required to create a reinforcement learning trading system. Also, we introduce AutoML, a powerful service on Google Cloud Platform for training machine learning models with minimal coding.
What's included
10 videos1 app item
Instructor
Instructor ratings
4.0 (34 ratings)
Recommended if you're interested in Machine Learning
University of Illinois Urbana-Champaign
Corporate Finance Institute
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3.5
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Showing 3 of 233
GY
4
Reviewed on Jul 1, 2022
I look forward to examples of integration of decision based on reinforcement learning and algo-trading logic
RS
4
Reviewed on Jul 12, 2021
A touhg and very advanced course, with an amazing Google Cloud Platform !!!!
GS
5
Reviewed on Mar 6, 2020
Great introduction to some very interesting concepts. Lots of hands on examples, and plenty to learn
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