1. Keras 2.x projects : 9 projects demonstrating faster experimentation of neural network and deep learning applications using Keras /: 9 projects demonstrating faster experimentation of neural network and deep learning applications using Keras. (2018) Authors: Ciaburro, Giuseppe Record Type: Book Extent: 1 online resource (1 volume), illustrations View Content: Available online (eLD content is only available in our Reading Rooms) ↗
2. Deep reinforcement learning for wireless networks. ([2019]) Authors: Yu, F. Richard; He, Ying Record Type: Book Extent: 1 online resource View Content: Available online (eLD content is only available in our Reading Rooms) ↗
3. Design of experiments for reinforcement learning. (2015) Authors: Gatti, Christopher Record Type: Book Extent: 1 online resource (196 pages), illustrations View Content: Available online (eLD content is only available in our Reading Rooms) ↗
4. Reinforcement learning : with Open AI, TensorFlow and Keras using Python /: with Open AI, TensorFlow and Keras using Python. ([2018]) Authors: Nandy, Abhishek; Biswas, Manisha Record Type: Book Extent: 1 online resource View Content: Available online (eLD content is only available in our Reading Rooms) ↗
5. Reinforcement learning for optimal feedback control : a Lyapunov-based approach /: a Lyapunov-based approach. (2018) Authors: Kamalapurkar, Rushikesh; Walters, Patrick; Rosenfeld, Joel; Dixon, Warren E, 1972- Record Type: Book Extent: 1 online resource (xvi, 293 pages), illustrations View Content: Available online (eLD content is only available in our Reading Rooms) ↗
6. Practical reinforcement learning : develop self-evolving, intelligent agents with OpenAI Gym, Python, and Java /: develop self-evolving, intelligent agents with OpenAI Gym, Python, and Java. (2017) Authors: Akhtar, Farrukh S. M Record Type: Book Extent: 1 online resource (1 volume), illustrations View Content: Available online (eLD content is only available in our Reading Rooms) ↗
7. The reinforcement learning workshop : learn how to apply cutting-edge reinforcement learning algorithms to your own machine learning models /: learn how to apply cutting-edge reinforcement learning algorithms to your own machine learning models. (2020) Authors: Palmas, Alessandro; Ghelfi, Emanuele; Dr, Petre, Alexandra Galina; Kulkarni, Mayur; N.S., Anand; Nguyễn, Quân; Sen, Aritra; So, Anthony; Basak, Saikat Record Type: Book Extent: 1 online resource View Content: Available online (eLD content is only available in our Reading Rooms) ↗
8. Foundations of reinforcement learning with applications in finance. (2022) Authors: Rao, Ashwin; Jelvis, Tikhon Record Type: Book Extent: 1 online resource, illustrations (black and white) View Content: Available online (eLD content is only available in our Reading Rooms) ↗
9. Deep reinforcement learning fundamentals, research and applications /: fundamentals, research and applications. (2020) Other Names: Dong, Hao; Ding, Zihan; Zhang, Shanghang Record Type: Book Extent: 1 online resource (526 p.) View Content: Available online (eLD content is only available in our Reading Rooms) ↗
10. Deep reinforcement learning hands-on : apply modern RL methods to practical problems of chatbots, robotics, discrete optimization, web automation, and more /: apply modern RL methods to practical problems of chatbots, robotics, discrete optimization, web automation, and more. (2020) Authors: Lapan, Maxim Record Type: Book Extent: 1 online resource, illustrations (black and white) View Content: Available online (eLD content is only available in our Reading Rooms) ↗