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Machine Learning For Absolute Beginners (2017)

Please note that this book is not a sequel to the First Edition, but rather a restructured and revamped version of the First Edition.

Ready to crank up a virtual server and smash through petabytes of data? Want to add ‘Machine

Learning’ to your LinkedIn profile?

Well, hold on there…

Before you embark on your epic journey into the world of machine learning, there is some theory and statistical principles to march through first.

But 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 book provides a practical and high-level introduction to the practical components and statistical concepts found in machine learning.

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Machine Learning for Beginners (2019)

Imagine a world where computing systems understand people and the world around us them to a point where they can notice patterns, collect data, interpret it and give recommendations to solve real world problems with high level of precision.

It sounds like science fiction but it is happening in healthcare, agriculture, cyber security, facial recognition, targeting and retargeting customers in online advertising, recommending specific products, stories, videos, text etc., self-driving cars, real time pricing, predicting human behavior and much more.

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Machine Learning Refined (2020)

With its intuitive yet rigorous approach to machine learning, this text provides students with the fundamental knowledge and practical tools needed to conduct research and build data-driven products.

The authors prioritize geometric intuition and algorithmic thinking, and include detail on all the essential mathematical prerequisites, to offer a fresh and accessible way to learn.

Practical applications are emphasized, with examples from disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology.

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Practical Machine Learning with Rust (2020)

This book is all about exploring Machine Learning in Rust lang. We will learn about the intricacies of creating machine learning applications and how they fit in the Rust worldview. We will start from the very beginning by understanding some of the important concepts of Machine Learning as well as the basics of Rust lang.

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PyTorch Pocket Reference (2021)

PyTorch has, no doubt, enabled some of the finest advances in deep learning and AI. It’s free to download and use, and with it anyone with a computer or internet connection can run AI experiments. In addition to more comprehensive references like this one, there are many free and inexpensive training
courses, blog articles, and tutorials that can help you. Anyone can get started using PyTorch for machine learning and AI.

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