- Book
- August 2021
- 320 Pages
- Book
- August 2021
- 256 Pages
- Book
- August 2021
- 528 Pages
- Book
- January 2021
- 320 Pages
- Book
- October 2020
- 544 Pages
- Book
- September 2020
- 272 Pages
- Book
- April 2020
- 336 Pages
- Book
- February 2020
- 496 Pages
- Book
- December 2019
- 672 Pages
- Book
- November 2019
- 640 Pages
- Book
- October 2019
- 528 Pages
- Book
- June 2019
- 320 Pages
- Book
- September 2018
- 800 Pages
- Book
- December 2024
- 272 Pages
- Book
- May 2022
- 432 Pages
- Book
- August 2022
- 304 Pages
Reinforcement Learning (RL) is a type of Machine Learning (ML) and Data Mining that focuses on taking suitable actions to maximize rewards in a given environment. It is an area of ML that has been gaining traction in recent years, as it has been used to solve complex problems in robotics, gaming, and autonomous driving. RL algorithms are based on trial and error, where an agent interacts with its environment and learns from the feedback it receives. This feedback is used to update the agent’s policy, which is then used to determine the next action.
RL is used in a variety of industries, such as finance, healthcare, and manufacturing. It is also used to optimize decision-making processes, such as scheduling, resource allocation, and inventory management.
Some companies in the RL market include DeepMind, OpenAI, Google, Microsoft, IBM, and NVIDIA. Show Less Read more