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Probabilistic Machine Learning: An Introduction (Adaptive Computation and Machine Learning series) free ebook download

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Computer Science

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Date:	2021	Format:	epub	Language:	English	ISBN/ASIN:	0262046822
Pages:	864	OCR:		Quality:		ISBN13:
Uploader:	gestalt	Upload Date:	3/13/2022 9:22:24 PM

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A detailed and up-to-date introduction to machine learning, presented through the unifying lens of probabilistic modeling and Bayesian decision theory.

This book offers a detailed and up-to-date introduction to machine learning (including deep learning) through the unifying lens of probabilistic modeling and Bayesian decision theory. The book covers mathematical background (including linear algebra and optimization), basic supervised learning (including linear and logistic regression and deep neural networks), as well as more advanced topics (including transfer learning and unsupervised learning). End-of-chapter exercises allow students to apply what they have learned, and an appendix covers notation.
 
grew out of the authors 2012 book, . More than just a simple update, this is a completely new book that reflects the dramatic developments in the field since 2012, most notably deep learning. In addition, the new book is accompanied by online Python code, using libraries such as scikit-learn, JAX, PyTorch, and Tensorflow, which can be used to reproduce nearly all the figures  this code can be run inside a web browser using cloud-based notebooks, and provides a practical complement to the theoretical topics discussed in the book. This introductory text will be followed by a sequel that covers more advanced topics, taking the same probabilistic approach.
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	Title	Link	Password	Size (MB)	Thank to	Inform Admin
3101594	Book	https://nitro.download/view/08103F6444FB...		0.00	gestalt

Tags: Adaptive Computation Introduction Learning Machine Probabilistic

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Probabilistic Machine Learning: An Introduction (Adaptive Computation and Machine Learning series) free ebook download

Category: Computer Science

Description: Click to see full description

Category:
Computer Science