04848nam a2200565 i 4500 on1347020175 EBZ 20260709112158.0 m d cr cnu|||||||| 221009t20232023caua ob 001 0 eng d 9781098122478 (electronic bk.) 109812247X (electronic bk.) 9781098122461 (electronic bk.) 1098122461 (electronic bk.) 1098125975 (paperback) 9781098125974 (paperback) 9781098125967 O'Reilly Media 8FF24866-5EDE-47E6-A85A-3C8376264084 OverDrive, Inc. http://www.overdrive.com EBZ eng EBZ MAIN Q325.5 QA76.73.P98 G45 2023eb 006.3/1 23/eng/20221011 Géron, Aurélien, author. https://id.oclc.org/worldcat/entity/E39PCjB9FgDVqV7Xf8QMYKMdHy https://isni.org/isni/0000000418957775 Hands-on Machine Learning with Scikit-Learn, Keras and TensorFlow : Concepts, tools, and techniques to build intelligent systems / Aurélien Géron. Third edition. Sebastopol, CA : O'Reilly Media, Inc., [2023] ©2023 1 online resource (xxv, 834 pages) : illustrations (chiefly color) text txt rdacontent still image sti rdacontent computer c rdamedia online resource cr rdacarrier textual sapdv EBSCOhost Includes bibliographical references and index. The fundamentals of machine learning. The machine learning landscape ; End-to-end machine learning project ; Classification ; Training models ; Support vector machines ; Decision trees ; Ensemble learning and random forests ; Dimensionality reduction ; Unsupervised learning techniques -- Neural networks and deep learning. Introduction to artificial neural networks with Keras ; Training deep neural networks ; Custom models and training with TensorFlow ; Loading and preprocessing data with TensorFlow ; Deep computer vision using convolutional neural networks ; Processing sequences using RNNs and CNNs ; Natural language processing with RNNs and attention ; Autoencoders, GANs, and diffusion models ; Reinforcement learning ; Training and deploying TensorFlow models at scale. "Through a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This bestselling book uses concrete examples, minimal theory, and production-ready Python frameworks (Scikit-Learn, Keras, and TensorFlow) to help you gain an intuitive understanding of the concepts and tools for building intelligent systems. With this updated third edition, author Aurélien Géron explores a range of techniques, starting with simple linear regression and progressing to deep neural networks. Numerous code examples and exercises throughout the book help you apply what you've learned. Programming experience is all you need to get started. Use Scikit-learn to track an example ML project end to end Explore several models, including support vector machines, decision trees, random forests, and ensemble methods Exploit unsupervised learning techniques such as dimensionality reduction, clustering, and anomaly detection Dive into neural net architectures, including convolutional nets, recurrent nets, generative adversarial networks, autoencoders, diffusion models, and transformers Use TensorFlow and Keras to build and train neural nets for computer vision, natural language processing, generative models, and deep reinforcement learning."-- Provided by publisher. EBSCOhost "EBSCO evaluates our products based on the Web Content Accessibility Guidelines (WCAG) and the related Section 508 and EN 301 549 regulations in the US and EU. Most EBSCO products are substantially conformant with WCAG 2.2 level AA." Source: https://connect.ebsco.com/s/article/EBSCO-VPATs?language=en_US. Last accessed April 22, 2025. Description based print version record and online resource (ProQuest Ebook Central, viewed September 26, 2024). WorldCat record variable field(s) change: 050 TensorFlow. Machine learning. Artificial intelligence. Python (Computer program language) artificial intelligence. aat Print version: 1098125975 9781098125974 (DLC) 2023549175 https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=3406174 CLICK HERE to access ebook ddc EBOOK 2714 2714