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.
Familiarization with basic concepts in Machine Learning and Financial Markets; advanced competency in Python Programming.
- 5 stars34.67%
- 4 stars26.13%
- 3 stars19.59%
- 2 stars7.53%
- 1 star12.06%
來自REINFORCEMENT LEARNING FOR TRADING STRATEGIES的熱門評論
After the first two courses, this one grabs you into the reinforcement learning spectrum. This topic has been revealing to me and its applications to trading
Great introduction to some very interesting concepts. Lots of hands on examples, and plenty to learn
I look forward to examples of integration of decision based on reinforcement learning and algo-trading logic
perhaps an applied trading notebook would have been nice...I understand that liability issues might have arisen, but there might have been a reasonable avenue with repeat disclaimers, etc