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.
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课程信息
Familiarization with basic concepts in Machine Learning and Financial Markets; advanced competency in Python Programming.
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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.
您将获得的技能
- Reinforcement Learning Model Development
- Reinforcement Learning Trading Algorithm Optimization
- Reinforcement Learning Trading Strategy Development
- Reinforcement Learning Trading Algo Development
Familiarization with basic concepts in Machine Learning and Financial Markets; advanced competency in Python Programming.
对员工进行热门技能培训能否为您的公司带来益处?
体验 Coursera 企业版授课大纲 - 您将从这门课程中学到什么
Introduction to Course and Reinforcement Learning
Neural Network Based Reinforcement Learning
Portfolio Optimization
审阅
- 5 stars34.31%
- 4 stars25.49%
- 3 stars19.60%
- 2 stars7.84%
- 1 star12.74%
来自REINFORCEMENT LEARNING FOR TRADING STRATEGIES的热门评论
Provide the idea and method of RL for trading, but seems like less practice knowledge for the trading. hope can add more detail for for the trading build up. overall the course are good.
Good course introducing concepts in RL. Wish course provided more examples of using RL in stock prediction.
Great introduction to some very interesting concepts. Lots of hands on examples, and plenty to learn
The course covers broad and important topics on using AI for trading, but one will need to dig more quite extensively on alternative sources to deepen one's understanding
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