| 000 -LEADER |
|---|
| fixed length control field |
03633nam a2200301 4500 |
| 001 - CONTROL NUMBER |
|---|
| control field |
1124925244 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
APU |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20210107023046.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
191024s2019 caua 001 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9781492032649 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
1492032646 |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
JBL |
| Language of cataloging |
eng |
| Transcribing agency |
APU |
| Modifying agency |
SF |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER |
|---|
| Classification number |
Q325.5 |
| Item number |
.G46 2019 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Géron, Aurélien, |
| 9 (RLIN) |
46197 |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Hands-on machine learning with Scikit-Learn, Keras, and TensorFlow : |
| Remainder of title |
concepts, tools, and techniques to build intelligent systems / |
| Statement of responsibility, etc |
Aurélien Géron. |
| 250 ## - EDITION STATEMENT |
|---|
| Edition statement |
2nd ed. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
|---|
| Place of publication, distribution, etc |
Beijing : |
| Name of publisher, distributor, etc |
O'Reilly, |
| Date of publication, distribution, etc |
c2019. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xxv, 819 pages. : |
| Other physical details |
color illustration ; |
| Dimensions |
24 cm. |
| 500 ## - GENERAL NOTE |
|---|
| General note |
"2nd edition updated for TensorFlow 2"--Page 1 of cover |
| 500 ## - GENERAL NOTE |
|---|
| General note |
Includes index |
| 505 0# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
Part I, 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 -- Part II, 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 ; Representation learning and generative learning using autoencoders and GANs ; Reinforcement learning ; Training and deploying TensorFlow models at scale ; Exercise solutions ; Machine learning project checklist ; SVM dual problem ; Autodiff ; Other popular ANN architectures ; Special data structures ; TensorFlow graphs |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc |
Through a series of recent 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. The updated edition of this best-selling book uses concrete examples, minimal theory, and two production-ready Python frameworks-Scikit-Learn and TensorFlow 2-to help you gain an intuitive understanding of the concepts and tools for building intelligent systems. Practitioners will learn a range of techniques that they can quickly put to use on the job. Part 1 employs Scikit-Learn to introduce fundamental machine learning tasks, such as simple linear regression. Part 2, which has been significantly updated, employs Keras and TensorFlow 2 to guide the reader through more advanced machine learning methods using deep neural networks. With exercises in each chapter to help you apply what you've learned, all you need is programming experience to get started. NEW FOR THE SECOND EDITION:Updated all code to TensorFlow 2Introduced the high-level Keras APINew and expanded coverage including TensorFlow's Data API, Eager Execution, Estimators API, deploying on Google Cloud ML, handling time series, embeddings and more With Early Release ebooks, you get books in their earliest form-the author's raw and unedited content as he or she writes-so you can take advantage of these technologies long before the official release of these titles. You'll also receive updates when significant changes are made, new chapters are available, and the final ebook bundle is released |
| 630 00 - SUBJECT ADDED ENTRY--UNIFORM TITLE |
|---|
| Uniform title |
TensorFlow. |
| 9 (RLIN) |
46198 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Machine learning. |
| 9 (RLIN) |
46199 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Artificial intelligence. |
| 9 (RLIN) |
46200 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Python (Computer program language) |
| 9 (RLIN) |
46201 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
|
| Koha item type |
Book |
