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Python Reinforcement Learning Projects

You're reading from   Python Reinforcement Learning Projects Eight hands-on projects exploring reinforcement learning algorithms using TensorFlow

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Product type Paperback
Published in Sep 2018
Publisher Packt
ISBN-13 9781788991612
Length 296 pages
Edition 1st Edition
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Authors (3):
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Sean Saito Sean Saito
Author Profile Icon Sean Saito
Sean Saito
Rajalingappaa Shanmugamani Rajalingappaa Shanmugamani
Author Profile Icon Rajalingappaa Shanmugamani
Rajalingappaa Shanmugamani
Yang Wenzhuo Yang Wenzhuo
Author Profile Icon Yang Wenzhuo
Yang Wenzhuo
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Toc

Summary


In conclusion, machine learning can be applied to several industries and can be applied very efficiently in financial markets, as you saw in this chapter. We can combine different models, as we did with reinforcement learning and time series, to produce stronger models that suit our use cases. We discussed the use of reinforcement learning and time series to predict the stock market. We worked with an actor-critic model that determined the best action, based on the state of the stock prices, with the aim of maximizing profits. In the end, we obtained a result that boasted an overall profit and included increasing profits over time, indicating that the agent learned more with each state.

In the next chapter, you will learn about the future areas of work. 

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