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This is a pragmatic book that presents some of the most important topics about the Python programming language in a concise form, designed to make it easier to find out the most relevant information bits in a context where resources abound and frequently are just too overwhelming.

Deep Reinforcement Learning is a somewhat new field within Machine Learning or Artificial Intelligence (you may pick your favorite term between these two, even if they’re not strictly the same), which combines Deep Learning and Reinforcement Learning and is based on the general idea that an agent can learn by observing its actions and their consequences. No, it is not a return to John B. Watson and B. F. Skinner’s behavioral psychology. We are talking, instead, about a set of pretty advanced machine learning algorithms that, when properly mastered, allow computers to achieve remarkable results in some complex tasks. That’s what this book is about, so let’s dive in…

Those among you who have already learned some Python or may even have used it in some projects will certainly have heard the expression “Pythonic Code”, which conveys a general and somewhat wide meaning of “clean code and good software development practices in the context of Python”. With Effective Python, the author presents you with nothing less than 90 practical examples on how to adopt a pythonic developer mindset and how to write better Python code.

Machine learning, one of the hottest tech topics of today, is being used more and more. Sometimes as the best tool for the job, other times perhaps as a buzzword that is mainly used as a way to make a product look cooler. However, without knowing what ML is and how it works behind the scenes, it’s very easy to get lost. But this book does a great job in guiding you all the way up from very simple math concepts to some sophisticated machine learning techniques.

If you have been following beginner or even intermediate guides on Python and are starting to feel the need for more advanced learning, this book may be the one you have been looking for.

This is a book written while having in mind those who already have some object-oriented programming background but are willing to get into Python and (especially) Artificial Intelligence and Data Science.

This is an interesting book about Python, but not the usual handbook or cookbook style. If you already know the basics and want to discover new details about this programming language, or if you want to check if you really have a solid grasp on it, this book will give you some insightful, bite-size, tips and tricks.