If you practice along with the book for a substantial time, you would end up building machine learning models on your own. This book helps you cover the basics of Machine Learning. Knowledge of Machine Learning is critical for a data science professional. Introduction to Machine Learning with Python: A Guide for Data Scientists – By Andreas C. This book covers core concepts and will help you build a strong foundation for data science. If you are studying probability for the very first time, you just need to spend some extra time with it. If you have studied basic probability in school, this book is a build upon it. It holds immense importance in the field of data science and this book will introduce you to the concepts by taking examples from real-life problems.
Next in line after statistics is probability. Introduction to Probability – By Joseph K. If you are starting from scratch, this book is for you. You can learn a lot about statistics in data science and could cover in-depth on topics like randomisation, distribution, sampling etc. It covers a vast range of topics critical to the field of data science in an easy to understand language. This book is ideal for absolute beginners. Practical Statistics for Data Scientists – By Peter Bruce and Andrew Bruce
Practical Statistics for Data Scientists.If you are considering making a move in this domain, or are a data science expert who wants to remain on top of things, here is a list of books for you to keep the ball rolling. As we see more and more companies adopting data science applications in their businesses, there is a surge in the requirement for skilled data science professionals. Data Science has emerged to become one of the most paid and highly reputed domains for professionals.
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