Data Science and Machine Learning-Test Bank

ISBN

1138492531

“This textbook is a well-rounded, rigorous, and informative work presenting the arithmetic behind modern machine finding out strategies. It hits all of the exact notes: the number of topics is up-to-date and wonderful for a course on data science for arithmetic faculty college students on the superior undergraduate or early graduate stage. This e book fills a sorely-needed gap throughout the current literature by not sacrificing depth for breadth, presenting proofs of predominant theorems and subsequent derivations, along with providing a copious amount of Python code. I solely need a e book like this had been spherical as soon as I first began my journey!” -Nicholas Hoell, School of Toronto “This could be a well-written e book that offers a deeper dive into data-scientific methods than many introductory texts. The writing is apparent, and the textual content material logically builds up regularization, classification, and selection bushes. Compared with its doable rivals, it carves out a singular space of curiosity. -Adam Loy, Carleton College The purpose of Data Science and Machine Learning: Mathematical and Statistical Methods is to supply an accessible, however full textbook supposed for faculty children smitten by gaining a higher understanding of the arithmetic and statistics that underpin the rich variety of ideas and machine finding out algorithms in data science. Key Choices: Focuses on mathematical understanding. Presentation is self-contained, accessible, and full. Intensive itemizing of exercise routines and worked-out examples. Many concrete algorithms with Python code. Full shade all by means of.   Extra Sources could also be found on the authors