000			01577nam a22002297a 4500
005			20251029164438.0
008			251029b |||||||| |||| 00| 0 eng d
020			_a9781633438750
082			_a006.31 _bBAB
100			_aBabushkin, Valerii _925933
245			_aMachine learning system design: _bwith end-to-end examples
260			_aShelter Island _bManning Publications _c2025
300			_axx, 351 p.
365			_aUSD _b59.99
520			_aFrom information gathering to release and maintenance, Machine Learning System Design guides you step-by-step through every stage of the machine learning process. Inside, you’ll find a reliable framework for building, maintaining, and improving machine learning systems at any scale or complexity. In Machine Learning System Design: With end-to-end examples you will learn: The big picture of machine learning system design Analyzing a problem space to identify the optimal ML solution Ace ML system design interviews Selecting appropriate metrics and evaluation criteria Prioritizing tasks at different stages of ML system design Solving dataset-related problems with data gathering, error analysis, and feature engineering Recognizing common pitfalls in ML system development Designing ML systems to be lean, maintainable, and extensible over time (https://www.manning.com/books/machine-learning-system-design)
650			_aData science
650			_aSmart technology collection _925931
650			_aBig data
650			_aBusiness analytics
700			_aKravchenko, Arseny _925934
942			_cBK _2ddc
999			_c10476 _d10476