An introduction to statistical learning  (English, Paperback, Usharani)

Being a data scientist in the tech industry is one of the most rewarding careers on the planet today. I went and studied actual job descriptions for data scientist roles at tech companies and I distilled those requirements down into the topics that you'll see in this course. Data Science and Machine Learning are really comprehensive. We'll start with a crash course on Python and do a review of some basic statistics and probability, but then we're going to dive right into over 60 topics in data mining and machine learning. That includes things such as Bayes' theorem, clustering, decision trees, regression analysis, experimental design; we'll look at them all. Some of these topics are really fun. If you're a software developer or programmer looking to transition into a career in data science, this course will teach you the hottest skills without all the mathematical notation and pretense that comes along with these topics. We're just going to explain these concepts and show you some Python code that actually works that you can dive in and mess around with to make those concepts sink home, and if you're working as a data analyst in the finance industry, this course can also teach you to make the transition into the tech industry. All you need is some prior experience in programming or scripting and you should be good to go.