As the title says, this book covers all the topics for probability & statistics in context of data science. While working on data science projects, I tried to look for a reference book which can give reader holistic view of probability & statistics useful for data science, but I could not find everything at one place. So every time, I used to look for the term or topic at various places and then used to relate it in context of data science. At the end, I started writing about these topics in my blog (https://medium.com/@rathi.ankit) as my notes on probability & statistics which were well received by data science community. This book is for people who are working in data science field and want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines.
The approach I have taken here is not to reinvent the wheel, so I try to give an intuitive understanding of each topic and if the user wants to dig further on that topic, he can refer to the companion GitHub notebook of this book, scan the QR code given in the book to get the link.
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Book Details
Publication Year
2019
Contributors
Author Info
Ankit Rathi is currently working as a Data Science Architect at SITA aero. He is a Data Science (ML/DL/AI) practitioner with more than a decade of demonstrated history of working in IT industry using Data & Analytics. His interest lies primarily in the theory & application of artificial intelligence, particularly in developing business applications for machine learning and deep learning. Ankit's work at SITA aero has revolved around designing FlightPredictor product & building the CoE capability. During his tenure as a Principal Consultant at Genpact HCM, Ankit architected and deployed machine learning pipelines for various clients across different industries like Insurance, F&A. He was previously a Tech Lead at RBS IDC where he designed and developed various data intensive applications in AML & Mortgages area.