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Book Watch is I Programmer's listing of new books and is compiled using publishers' publicity material. It is not to be read as a review where we provide an independent assessment. Some but by no means all of the books in Book Watch are eventually reviewed.
Machine Learning with R 3rd Ed (Packt)
Monday 22 Apr
This book provides a hands-on, readable guide to applying machine learning to real-world problems. Aimed at both experienced R users and developers new to the language, author Brett Lantz covers the topics needed to uncover key insights, make new predictions, and visualize data findings. This new 3rd edition updates the classic R data science book with newer and better libraries, advice on ethical and bias issues in machine learning, and an introduction to deep learning.
3D Printing: An Introduction (Mercury Learning)
Wednesday 17 Apr
This book is designed as an introduction to the field of 3D printing. It includes an overview of 3D printing technology in industry, education, and Do-It-Yourself. Author Stephanie Torta also takes a detailed look at the common 3D printers, materials, and software. Using full-color images throughout, the book shows how to set up printers and perform calibration tasks, including descriptions of printing methods, best practices, pitfalls to avoid, and how to finish a completed project.
Hands-On Unsupervised Learning Using Python (O'Reilly)
Monday 15 Apr
With a subtitle of "How to Build Applied Machine Learning Solutions from Unlabeled Data", this book shows how unsupervised learning can be applied to unlabeled datasets to discover meaningful patterns buried deep in the data, patterns that may be near impossible for humans to uncover. Author Ankur Patel provides practical knowledge on how to apply unsupervised learning using two simple, production-ready Python frameworks - scikit-learn and TensorFlow - using Keras with hands-on examples and code. He shows how to identify difficult-to-find patterns in data, detect anomalies, perform automatic feature engineering and selection, and generate synthetic datasets.
Learn Robotics with Raspberry Pi (No Starch Press)
Friday 12 Apr
This book shows how to build and code your own robot projects with just the Raspberry Pi microcomputer and a few easy-to-get components . Author Matt Timmons-Brown starts with instructions on building a two-wheeled robot powered by a Raspberry Pi minicomputer and then shows how to program it using Python. The book also shows how to improve your robot by adding increasingly advanced functionality until it can follow lines, avoid obstacles, and even recognize objects of a certain size and color using computer vision.
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