Machine Learning Mastery, 2016. — 179 p. The Python ecosystem with scikit-learn and pandas is required for operational machine learning. Python is the rising platform for professional machine learning because you can use the same code to explore different models in R&D then deploy it directly to production. In this mega Ebook written in the friendly Machine Learning Mastery style that you’re used to, learn exactly how to get started and apply machine learning using the Python ecosystem. You get: 178 p. PDF Ebook. 74 Python Recipes using scikit-learn and Pandas. 16 Step-by-Step Lessons. 3 End-to-End Projects.
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New York: Jason Brownlee., 2018. — 212 p. Linear algebra is a pillar of machine learning. You cannot develop a deep understanding and application of machine learning without it. In this new laser-focused Ebook written in the friendly Machine Learning Mastery style that you’re used to, you will finally cut through the equations, Greek letters, and confusion, and discover the...
Machine Learning Mastery, 2016. — 223 p. — ISBN: N\A Do you want to do machine learning using R, but you’re having trouble getting started? In this post you will complete your first machine learning project using R. In this step-by-step tutorial you will: Download and install R and get the most useful package for machine learning in R. Load a dataset and understand it’s...
2016. — 162 p. The book was designed to teach developers about machine learning algorithms. It includes both procedural descriptions of machine learning algorithms and step-by-step tutorials that show exactly how to plug-in numbers into the various equations and exactly what numbers to expect on the other side.
Packt Publishing, 2017. — 450 p. — ISBN: 978-1-78829-575-8. True PDF Complex statistics in Machine Learning worry a lot of developers. Knowing statistics helps you build strong Machine Learning models that are optimized for a given problem statement. This book will teach you all it takes to perform complex statistical computations required for Machine Learning. You will gain...
Packt Publishing, 2016. — 653 p. — ISBN10: 178439968X. — ISBN13: 978-1784399689 This book has been created for data scientists who want to see Machine learning in action and explore its real-world applications. Knowledge of programming (Python and R) and mathematics is advisable if you want to get started immediately. About This Book Fully-coded working examples using a wide...
MIT Press, 2016. — 802 p. A comprehensive introduction to neural networks and deep learning by leading researchers of this field. Written for two main target audiences: university students (undergraduate or graduate) learning about machine learning, and software engineers. This is a PDF compilation of online book (www.deeplearningbook.org) Who Should Read This Book? Historical...