Artificial Intelligence

Build, train, deploy, scale and maintain deep learning models. Understand ML infrastructure and MLOps using hands-on examples.

A very interesting book with experiments on real life data .

Python is a rich and powerful language, but many data scientists merely scratch the surface, and often feel uncertain about what lies beneath.  This book will go deep into the heart of Python, to truly understand its components, and how we can stitch them together to build better scientific workflows and machine learning systems.

This book provides a holistic and complete view of the data strategy elements, enabling the practitioner at every step.

The book is intended to get you acquainted with the world of Supervised Machine Learning and does not assume previous knowledge of the field. The commonly leveraged Linear Regression technique used to provide predictions that are continuous in nature is detailed in the book. SAMPLE CODE INCLUDED!

The Expert Curve is about how expertise is achieved. With a comprehensive look into the science behind expertise, talent, prodigies, and training, The Expert Curve lays out the current understanding of how people learn to operate at expert levels in their fields and gives you the best tools to achieve expertise yourself.

You will learn that NumPy has very efficient arrays that are easy to use due to the powerful indexing mechanism. This book describes some of the more advanced and tricky indexing techniques.Also we will try to make an attempt to document the most essential methods that every user should know. NumPy has many methods to even mention in this book!

This 15x PDF collection is a compilation of the best cheat sheets created for my free Finxter Email Academy that teaches Python in byte-sized video and cheat sheet lessons.

市面上的深度学习书要么晦涩难懂，要么是平台使用说明书，只讲理论缺少实现或者只有编程缺少原理讲解，都很难让人理解深度学习的基本原理，本书采用理论讲解与代码实现的方式深入浅出地剖析了深度学习的技术原理和实现细节，教会读者如何从零编写一个深度学习库。内容包含了：梯度下降法、回归学习、前馈神经网络、卷积神经网络、循环神经网络、生成网络。

How to develop an Artificial Intelligence application? This book includes Agility foundations, engineering practices, real examples, and suggestions for implementing them in your company. Foreword by Jeff Sutherland, co-author of Scrum and the Agile Manifesto.

The battle for our collective identity, is continually waged, as no human has as of yet, been crowned as a sovereign king of all creation.

Computational Sense Making is new and exciting area of Applied AI with lot of research interest. In this book, we have attempted to give our readers an introduction of the topic with an implementation approach. This will help readers understand the topic in depth and apply computational sense making in different use cases.

The book explains the core concepts and terminologies of Descriptive Statistics using real-world examples. The book contains 17 practice problems, 2 quizzes, 36 graphical representations and numerous examples to enable effective learning and understanding of the concepts. Please check the bundle options with this book for better deals!