statistics and probability for data science khan academy

It focuses entirely on understanding real life influence of statistics using popular case studies. Hence, make sure you’ve got some basic knowledge of Python before buying this book. It is based on perform statistical analysis practically in Python. The author of this book is Alien B Downey. The algorithms have been implemented in R programming. This book, will introduce you to higher level algorithms such as Neural Networks, Bagging & Boosting, Kernel methods etc. Their first book ‘Introduction to Statistical Learning’ uncover the basics of statistics and machine learning. It is written by Trevor Hastie and Rob Tibshirani, Professors at Stanford University. This book is an advanced level of previous book. In addition to theory, this book also lay emphasis on using ML algorithms in real life setting. R users will get an advantage, since the practical aspects of algorithms have been demonstrated using R. Hence, you’ll learn about all popular supervised and unsupervised machine learning algorithms. The focus of this books is kept on connecting statistics concept with machine learning. This is a highly recommended book for practicing data scientists. Statistics Introduction to Statistical Learning If not, a link to amazon bookstore is provided. Note: Books which are made free to access by the registered authorities have been mentioned in this article. Hence, I’ve enlist only those books which will help you to connect with data science better. I understand, mathematics has no extreme. In this article, I’ve compiled a list of must read books on statistics and mathematics. So, if not anything else, try to become a great story explorer! More than just deriving accuracy, understanding & interpreting every metric, calculation behind that accuracy is important. Remember, every single ‘variable’ has a story to tell.

If you too aspire to work for such top companies in future, it is essential for you to develop a mathematical understanding of data science. Data science is simply the evolved version of statistics and mathematics, combined with programming and business logic. I’ve met many data scientists who struggle to explain predictive models statistically. Not just Google, other top companies (Amazon, Airbnb, Uber etc) in the world also prefer candidates with strong fundamentals rather than mere know-how in data science.

The selection process of data scientists at Google gives higher priority to candidates with strong background in statistics and mathematics.

Statistics and probability for data science khan academy