A proper grasp of statistics is essential for any machine learning enthusiast to succeed in the competitive domain. Consequently, one should focus more on statistics than on the latest fancy techniques. The book — All of Statistics — consists of 24 chapters and covers every topic right from probability to statistical inference and statistical models and methods.

 Time series analysis has gain popularity due to its use cases in financial data, especially, in companies’ stock prediction, fraud detection in transactions, and more. Besides, it is now becoming an essential technique in data science due to the rise of streaming analytics in numerous business operations. Obtaining real-time insights while also comparing with the historical trends allow companies to quickly make informed decisions. 

The book includes 11 chapters on a wide range of time series techniques such as nonstationary and seasonal time series models, multivariate time series, state-space models, and forecasting methods.

 With more than 2.3 million downloads, this is one of the most popular data science books. The process of data mining has increasingly become essential for businesses to achieve rapidly grow by making decisions based on insights. Therefore, this book includes all principles for data mining to discover patterns in a colossal amount of data. Designed to help even the beginners, it covers an introduction to classification like Naive Bayes, Nearest Neighbour, Decision Tree, among others, along with detailed explanations.