Machine learning for absolute beginners : a plain English introduction / Oliver Theobald

Preface -- What is Machine Learning ? -- Machine Learning Categories -- The Machine Learning Toolbox -- Data Scrubbing Setting up your data -- Linear Regression -- Logistic Regression -- k-Nearest -- k-Means Clustering -- Bias & Variance -- Support Vector Machines -- Artificial Neural Networks -- Decision Trees -- Ensemble Modeling -- Development Environment -- Building a Model in Python -- Model Optimization -- Next Steps -- Thank You -- Bug Bounty -- Further Resources -- Appendix: Introduction to Python.

Machine Learning for Absolute Beginners has been written and designed for absolute beginners. This means plain English explanations and no coding experience required. Where core algorithms are introduced, clear explanations and visual examples are added to make it easy and engaging to follow along at home. This title opens with a general introduction to machine learning from a macro level. The second half of the book is more practical and dives into introducing specific algorithms applied in machine learning, including their pros and cons. At the end of the book, I share insights and advice on further learning and careers in this space