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Thinking Data Science: A Data Science Practitioner's Guide
Hardcover
Series: Springer Applied Machine Learning
General ComputersProbability & Statistics
ISBN13: 9783031023620
Publisher: Springer
Published: Mar 2 2023
Pages: 358
Weight: 1.56
Height: 0.88 Width: 6.14 Depth: 9.21
Language: English
This definitive guide to Machine Learning projects answers the problems an aspiring or experienced data scientist frequently has: Confused on what technology to use for your ML development? Should I use GOFAI, ANN/DNN or Transfer Learning? Can I rely on AutoML for model development? What if the client provides me Gig and Terabytes of data for developing analytic models? How do I handle high-frequency dynamic datasets? This book provides the practitioner with a consolidation of the entire data science process in a single Cheat Sheet.
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