Machine Learning Python - 2 BOOK BUNDLE!! Book 1: Artificial Intelligence with Python

It is more than apparent that artificial intelligence techniques and practices will navigate the changes in the near future and simply shape the world. It is fair to say that AP is leading approach when it comes to the various scientific fields as well as various industries and today, it is almost impossible the world without advancements in the artificial intelligence field. Experts and scientists both agree that artificial intelligence is the field which will most certainly shape our economic future, automotive industry, health care, cybersecurity as well as cybercrime. Over the coming decades, AI will greatly impact every aspect of our lives including our work, careers, education, care for elderly and much more. Eventually, it will alter the world completely, as machines will pursue complex goals independently of their creators. AI tools have become mainstream tools when it comes to the various industries and science fields since these tools greatly reduce costs, increase profits and even save lives. If you understand the basic concept behind different AI techniques and approaches, you will be able to greatly benefit from it in various aspects. In order to maximize the benefits of AI advancements, you have to be ready to embark on different challenges. However, with this book, you will be able to overcome challenges and the reward is a success.

• Different artificial intelligence approaches and goals
• How to define AI system
• Basic AI techniques
• Reinforcement learning
• How to build a recommender system
• Genetic and logic programming
• And much, much more...

Reinforcement learning is one of those data science fields, which will most certainly shape the world. The changes are already visible since we have self-driving cars, robots and much more we used to see only in some futuristic movies. Reinforcement learning is widely used machine learning technique, a computational approach when it comes to the different software agents, which are trying to maximize the total amount of possible reward they receive while interacting with some uncertain as well as very complex environments.

This book is divided into seven chapters in which you will get to reinforcement techniques and methodology better. The first chapters will introduce you to the main concept laying being reinforcement learning techniques. Further, you will see what is the difference between reinforcement learning and other machine learning techniques. The book also provides some of the basic solution methods when it comes to the Markov decision processes, dynamic programming, Monte Carlo methods and temporal difference learning.

• Types of fundamental machine learning algorithms in comparison to reinforcement learning
• Essentials of reinforcement learning process
• Marko decision processes and basic parameters
• How to integrate reinforcement learning algorithm using OpenAI Gym
• How to integrate Monte Carlo methods for prediction
• Monte Carlo tree search
• Dynamic programming in Python for policy evaluation, policy iteration and value iteration
• Temporal difference learning or TD
• And much, much more...