E-Books →Data Science with R Beginner to Expert

The book takes you through data analysis, underlying mathematics, and prediction modeling. The mathematics chapter covers linear algebra, probability, and probability distributions. These are the foundations for learning machine learning. The book covers all the aspects of data science, from data collection to the presentation of prediction models. It covers data preparation, Regression, and Classification extensively. The chapters have to do exercises to practice machine learning.
The book has real datasets examples. The hands-on projects are a detailed step-by-step guide for data analysis and model creation. They provide a practical approach to applying data science techniques.
The book concludes with interview questions. Jumpstart your career after reading this book. Use the book for reference and revision before interviews.