Get Discount 5% Off
Subscribe to our newsletters now and stay up-to-date with new arrivals, updates and deals.
Gain a theoretical understanding to the most popular libraries in deep reinforcement learning (deep RL). This new edition focuses on the latest advances in deep RL using a learn-by-coding approach, allowing readers to assimilate and replicate the latest research in this field.
New agent environments ranging from games, and robotics to finance are explained to help you try different ways to apply reinforcement learning. A chapter on multi-agent reinforcement learning covers how multiple agents compete, while another chapter focuses on the widely used deep RL algorithm, proximal policy optimization (PPO). You'll see how reinforcement learning with human feedback (RLHF) has been used by chatbots, built using Large Language Models, e.g. ChatGPT to improve conversational capabilities.
You'll also review the steps for using the code on multiple cloud systems and deploying models on platforms such as Hugging Face Hub. The code is in Jupyter Notebook, which canbe run on Google Colab, and other similar deep learning cloud platforms, allowing you to tailor the code to your own needs.
Whether it's for applications in gaming, robotics, or Generative AI, Deep Reinforcement Learning with Python will help keep you ahead of the curve.
Who This Book Is For
Software engineers and machine learning developers eager to sharpen their understanding of deep RL and acquire practical skills in implementing RL algorithms fromscratch.
Nimish is a seasoned entrepreneur and an angel investor, with a rich portfolio of tech ventures in SaaS Software and Automation with AI across India, the US and Singapore. He has over 30 years of work experience. Nimish ventured into entrepreneurship in 2006 after holding leadership roles at global corporations like PwC, IBM, and Oracle.
Nimish holds an MBA from Indian Institute of Management, Ahmedabad, India (IIMA), and a Bachelor of Technology in Electrical Engineering from Indian Institute of Technology, Kanpur, India (IITK).
You may return most new, unopened items within 30 days of delivery for a full refund. We'll also pay the return shipping costs if the return is a result of our error (you received an incorrect or defective item, etc.).
You should expect to receive your refund within four weeks of giving your package to the return shipper, however, in many cases you will receive a refund more quickly. This time period includes the transit time for us to receive your return from the shipper (5 to 10 business days), the time it takes us to process your return once we receive it (3 to 5 business days), and the time it takes your bank to process our refund request (5 to 10 business days).
If you need to return an item, simply login to your account, view the order using the "Complete Orders" link under the My Account menu and click the Return Item(s) button. We'll notify you via e-mail of your refund once we've received and processed the returned item.
We can ship to virtually any address in the world. Note that there are restrictions on some products, and some products cannot be shipped to international destinations.
When you place an order, we will estimate shipping and delivery dates for you based on the availability of your items and the shipping options you choose. Depending on the shipping provider you choose, shipping date estimates may appear on the shipping quotes page.
Please also note that the shipping rates for many items we sell are weight-based. The weight of any such item can be found on its detail page. To reflect the policies of the shipping companies we use, all weights will be rounded up to the next full pound.
Subscribe to our newsletters now and stay up-to-date with new arrivals, updates and deals.
Thanks for subscribing!
This email has been registered!
Product | SKU | Description | Collection | Availability | Product Type | Other Details |
---|