| 000 -LEADER |
|---|
| fixed length control field |
03583nam a22002537a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20220429052832.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
220429b ||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9781119642145 |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
CvSU-CCAT Campus Library. |
| Language of cataloging |
English. |
| Transcribing agency |
CvSU-CCAT Campus Library. |
| Description conventions |
rda. |
| 050 ## - LIBRARY OF CONGRESS CALL NUMBER |
|---|
| Classification number |
Q 325.5 |
| Item number |
B45 2020 |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Bell, Jason, author. |
| 9 (RLIN) |
4924 |
| 245 ## - TITLE STATEMENT |
|---|
| Title |
Machine learning : |
| Remainder of title |
hands-on for developer's and technical professionals / |
| Statement of responsibility, etc. |
Jason Bell. |
| 250 ## - EDITION STATEMENT |
|---|
| Edition statement |
Second edition. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
|---|
| Place of publication, distribution, etc. |
Indianapolis, Indiana : |
| Name of publisher, distributor, etc. |
John Wiley & Sons, Inc., |
| Date of publication, distribution, etc. |
c2020. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xxxi, 400 pages : |
| Other physical details |
illustrations ; |
| Dimensions |
23 cm |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc. note |
Includes index. |
| 505 ## - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
Chapter 1 : What is machine learning?<br/>Chapter 2 : Planning for machine learning<br/>Chapter 3 : Data acquisition techniques<br/>Chapter 4 : Statistics, linear regression, and randomness<br/>Chapter 5 : Working with decision trees<br/>Chapter 6 : Clustering<br/>Chapter 7 :Association rules learning<br/>Chapter 8 : Support Vector machines<br/>Chapter 9 : Artificial Neural Networks<br/>Chapter 10 : Machine learning with text document<br/>Chapter 11 : Machine learning with images<br/>Chapter 12 : Machine Learning Streaming with Kafka<br/>Chapter 13 : Apache Spark<br/>Chapter 14 : Machine Learning with R |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
Dig deep into the data with a hands-on guide to machine learning with updated examples and more! Machine Learning: Hands-On for Developers and Technical Professionals provides hands-on instruction and fully-coded working examples for the most common machine learning techniques used by developers and technical professionals. The book contains a breakdown of each ML variant, explaining how it works and how it is used within certain industries, allowing readers to incorporate the presented techniques into their own work as they follow along. A core tenant of machine learning is a strong focus on data preparation, and a full exploration of the various types of learning algorithms illustrates how the proper tools can help any developer extract information and insights from existing data. The book includes a full complement of Instructor's Materials to facilitate use in the classroom, making this resource useful for students and as a professional reference. At its core, machine learning is a mathematical, algorithm-based technology that forms the basis of historical data mining and modern big data science. Scientific analysis of big data requires a working knowledge of machine learning, which forms predictions based on known properties learned from training data. Machine Learning is an accessible, comprehensive guide for the non-mathematician, providing clear guidance that allows readers to: Learn the languages of machine learning including Hadoop, Mahout, and Weka Understand decision trees, Bayesian networks, and artificial neural networks Implement Association Rule, Real Time, and Batch learning Develop a strategic plan for safe, effective, and efficient machine learning By learning to construct a system that can learn from data, readers can increase their utility across industries. Machine learning sits at the core of deep dive data analysis and visualization, which is increasingly in demand as companies discover the goldmine hiding in their existing data. For the tech professional involved in data science, Machine Learning: Hands-On for Developers and Technical Professionals provides the skills and techniques required to dig deeper |
| 546 ## - LANGUAGE NOTE |
|---|
| Language note |
In English text. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Machine learning. |
| 9 (RLIN) |
301 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
|
| Koha item type |
Book |
| Classification part |
Q 325.5 B45 2020 |
| Call number prefix |
CIR |
