Springer An Introduction to Statistical Learning: with Applications in R

This book is quite fantastic for an introductory level. I have a specialised training in mathematics and this books puts me up to date on several topics and algorithms without having to deal much time in the mathematical technicalities (for that, there are specialised treatises on each subject). The R code is quite good and although I think some of their advice is not appropriate (e.g. the attach function is in R only for legacy purposes but shouldn't be used since it overrides other functions, including base, aka default, functions), it is workable and so it's a great investment. The book is introductory focusing mostly on intuition and how to do, little time is spent in mathematical formalities, so that's a plus. I think there is a NEWER edition than the one I reviewed but otherwise I suspect the newer edition will be just better. Recommended.

This book is unparalleled in its coverage of Statistical/Machine Learning. It is comprehensive, easy to understand, and provides numerous examples to aid in comprehension. It also helps develop intuition and serves as a foundation for more mathematically advanced ML topics. Tip: Even if you prefer Python over R, consider using this book for theory and finding other resources for Python implementations.

Es un libro introductorio, pero que toca las bases matemáticas de los métodos estadísticos mas utilizados en análisis de datos.

Reprend les bases. Un livre que tout data scientist se doit de maitriser sur le bout des doigts. Très abbordable d'un point de vu mathématique.

Este livro contém a base de muitos métodos estatísticos utilizados em análise de dados: regressão, classificação, clusterização. Trata-se de uma introdução, sem matemática avançada, contendo os fundamentos que todo cientista de dados deveria saber.Dito isto, o livro é excelente, de leitura fácil e surpreendentemente agradável, sem deixar o rigor conceitual de lado. Há diversos exemplos e o encadeamento dos assuntos segue uma lógica bem interessante.Como bônus, ao final de cada capítulo há códigos e exercícios em R para que o leitor também possa "botar a mão na massa".