Machine Learning with Python for Everyone brings together all they’ll need to succeed: a practical understanding of the machine learning process, accessible code, skills for implementing that process with Python and the scikit-learn library, and real expertise in using learning systems intelligently.

Look around you. Artificial intelligence is no longer just a futuristic notion. It's here right now--in software that senses what we need, supply chains that "think" in real time, and robots that respond to changes in their environment. Twenty-first-century pioneer companies are already using AI to innovate and grow fast. The bottom line is this: Businesses that understand how to harness AI can surge ahead. Those that neglect it will fall behind. Which side are you on?

The book covers a broad array of topics not usually included in introductory machine learning texts, including supervised learning, Bayesian decision theory, parametric methods, semiparametric methods, nonparametric methods, multivariate analysis, hidden Markov models, reinforcement learning, kernel machines, graphical models, Bayesian estimation, and statistical testing.

Rather than spend $30-$50 USD on a dense long textbook, you may want to read this book first. As a clear and concise alternative to a textbook, this short book offers a practical and high-level introduction to the practical components and statistical concepts found in machine learning.

The book Machine Learning: Hands-On for Developers and Technical Professionals contains a breakdown of each ML variant, explaining how it works and how it is used within certain industries, allowing readers to incorporate the presented techniques into their own work as they follow along.

Designed for quick access on the job, Machine Tools Handbook explains in detail how to carry out basic and advanced machine tool operations and functions, providing a wealth of machine tool exercises to test and improve the performance of machinists.

If you're looking to make a career move from programmer to AI specialist, this is the ideal place to start. Based on Laurence Moroney's extremely successful AI courses, this introductory book provides a hands-on, code-first approach to help you build confidence while you learn key topics.

This Practical Book Shows You How. By Using Concrete Examples, Minimal Theory, And Two Production-Ready Python Frameworks―Scikit-Learn And Tensorflow―Author Aurélien Géron Helps You Gain An Intuitive Understanding Of The Concepts And Tools For Building Intelligent Systems

This is a Beginner Level story in a series of ELT readers comprising a wide range of titles - some original and some simplified - from modern and classic novels, and designed to appeal to all age-groups, tastes and cultures.

Provides basic knowledge of machine tools. Basic programs of numerically controlled machining machines. Introducing new technology and manufacturing process of machine tools.