000			02050nam a22002297a 4500
005			20251023145526.0
008			251023b |||||||| |||| 00| 0 eng d
020			_a9781837636303
028			_aTechnical Bureau India _b4794/23, 1st Floor, Eye 7, Ansari Road, New delhi _cTB1969 _d15/10/2025
082			_a005.7 OZD
100			_aOzdemir, Sinan.
245			_aPrinciples of Data Science _c/ Sinan Ozdemir.
260			_aBirmingham _b : Packet _c, 2016.
300			_axix, 305p. _c: 24cm.
365			_b2100
520			_aPrinciples of Data Science bridges mathematics, programming, and business analysis, empowering you to confidently pose and address complex data questions and construct effective machine learning pipelines. This book will equip you with the tools to transform abstract concepts and raw statistics into actionable insights. Starting with cleaning and preparation, you'll explore effective data mining strategies and techniques before moving on to building a holistic picture of how every piece of the data science puzzle fits together. Throughout the book, you'll discover statistical models with which you can control and navigate even the densest or the sparsest of datasets and learn how to create powerful visualizations that communicate the stories hidden in your data. With a focus on application, this edition covers advanced transfer learning and pre-trained models for NLP and vision tasks. You'll get to grips with advanced techniques for mitigating algorithmic bias in data as well as models and addressing model and data drift. Finally, you'll explore medium-level data governance, including data provenance, privacy, and deletion request handling. By the end of this data science book, you'll have learned the fundamentals of computational mathematics and statistics, all while navigating the intricacies of modern ML and large pre-trained models like GPT and BERT.
650			_aComputer Science
650			_aData Fluency
650			_aMachine Learning
700			_aSinan Ozdemir.
942			_cBOOK
999			_c66524 _d66524