Neil Lane

Probabilistic Machine Learning: An Introduction (Adaptive Computation and Mac...

Description: FASTSHIPPING HASSLEFREERETURNS SECUREPAYMENT EXCELLENTSERVICE Description 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. Probabilistic Machine Learning grew out of the author’s 2012 book, Machine Learning: A Probabilistic Perspective. 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. Publisher ‏ : ‎ The MIT Press Language ‏ : ‎ English Hardcover ‏ : ‎ 864 pages ISBN-10 ‏ : ‎ 0262046822 ISBN-13 ‏ : ‎ 978-0262046824 Item Weight ‏ : ‎ 1.25 pounds Dimensions ‏ : ‎ 0.04 x 0.04 x 0.04 inches SHIPPING Shipping All items fast! The majority of orders are shipped using USPS Priority Mail and UPS Ground if requested. There is an option at checkout to add a Signature of Delivery for extra security & peace of mind. This means you need to sign for your parcel. If you are not home, the courier will take it to your local post office for collection. We also offer expedited shipments upon request, we will quote the shipment and let you know of the estimated cost. If agreed we will process the order and add the shipping charge to your invoice. All items ordered by 3 PM EST will be shipped same day. We also are partnered with Ebay using the Global Shipping Program. We will ship internationally to any country that is a part of the program. "International buyers – please note: Import duties, taxes, and charges aren't included in the item price or postage cost. These charges are the buyer's responsibility. "Please check with your country's customs office to determine what these additional costs will be, prior to bidding or buying." 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FEEDBACK Our all customers are 100% satisfied. If you have any issues with your orders, please contact us to resolve it. We are happy to help you EXCHANGE CANCELLATION You need to send us an order cancellation request through eBay before the shipment made. once we have the request, we will approve it from our end and grant your full refund back to your account. CONTACT US Please send us an email via ebay. We will reply within 24 hours. Copyright © | All Rights Reserved

Price: 190 USD

Location: Philadelphia, Pennsylvania

End Time: 2024-09-23T17:13:17.000Z

Shipping Cost: 5.99 USD

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Probabilistic Machine Learning: An Introduction (Adaptive Computation and Mac...

Item Specifics

Restocking Fee: No

Return shipping will be paid by: Seller

All returns accepted: Returns Accepted

Item must be returned within: 30 Days

Refund will be given as: Money back or replacement (buyer's choice)

Book Title: Probabilistic Machine Learning HARDCOVER

Topic: Probabilistic Machine Learning HARDCOVER

Original Language: English

Unit Quantity: 1

ISBN: 0262046822

Number of Pages: 864 Pages

Language: English

Publication Name: Probabilistic Machine Learning : an Introduction

Publisher: MIT Press

Subject: Intelligence (Ai) & Semantics, Computer Science, General

Item Height: 1.5 in

Publication Year: 2022

Item Weight: 55.6 Oz

Type: Textbook

Item Length: 9.3 in

Author: Kevin P. Murphy

Subject Area: Computers, Science

Item Width: 8.3 in

Series: Adaptive Computation and Machine Learning Ser.

Format: Hardcover

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