Hands-On Machine Learning with C++. (Record no. 14965)
[ view plain ]
| 000 -LEADER | |
|---|---|
| fixed length control field | 03788nam a2200265uu 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20250710181501.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 250616s||||||||||||||||o||||||||||| |d |
| 024 80 - OTHER STANDARD IDENTIFIER | |
| Standard number or code | 9781789952476 |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | PACKT |
| Transcribing agency | PACKT |
| 041 ## - LANGUAGE CODE | |
| Language code of text/sound track or separate title | en |
| 044 ## - COUNTRY OF PUBLISHING/PRODUCING ENTITY CODE | |
| MARC country code | GB |
| 100 0# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Kirill Kolodiazhnyi |
| Relator term | author. |
| 245 00 - TITLE STATEMENT | |
| Title | Hands-On Machine Learning with C++. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | GB: |
| Name of publisher, distributor, etc. | Packt, |
| Date of publication, distribution, etc. | 2020-05-15. |
| 263 ## - PROJECTED PUBLICATION DATE | |
| Projected publication date | 2020-05-15 |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE | |
| Place of production, publication, distribution, manufacture | GB: |
| Name of producer, publisher, distributor, manufacturer | Packt, |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 530. |
| 377 ## - ASSOCIATED LANGUAGE | |
| Language code | en |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | <p><b>Implement supervised and unsupervised machine learning algorithms using C++ libraries such as PyTorch C++ API, Caffe2, Shogun, Shark-ML, mlpack, and dlib with the help of real-world examples and datasets</b></p><h4>Key Features</h4><ul><li>Become familiar with data processing, performance measuring, and model selection using various C++ libraries</li><li>Implement practical machine learning and deep learning techniques to build smart models</li><li>Deploy machine learning models to work on mobile and embedded devices</li></ul><h4>Book Description</h4>C++ can make your machine learning models run faster and more efficiently. This handy guide will help you learn the fundamentals of machine learning (ML), showing you how to use C++ libraries to get the most out of your data. This book makes machine learning with C++ for beginners easy with its example-based approach, demonstrating how to implement supervised and unsupervised ML algorithms through real-world examples.<br/><br/>This book will get you hands-on with tuning and optimizing a model for different use cases, assisting you with model selection and the measurement of performance. You’ll cover techniques such as product recommendations, ensemble learning, and anomaly detection using modern C++ libraries such as PyTorch C++ API, Caffe2, Shogun, Shark-ML, mlpack, and dlib. Next, you’ll explore neural networks and deep learning using examples such as image classification and sentiment analysis, which will help you solve various problems. Later, you’ll learn how to handle production and deployment challenges on mobile and cloud platforms, before discovering how to export and import models using the ONNX format.<br/><br/>By the end of this C++ book, you will have real-world machine learning and C++ knowledge, as well as the skills to use C++ to build powerful ML systems.<h4>What you will learn</h4><ul><li>Explore how to load and preprocess various data types to suitable C++ data structures</li><li>Employ key machine learning algorithms with various C++ libraries</li><li>Understand the grid-search approach to find the best parameters for a machine learning model</li><li>Implement an algorithm for filtering anomalies in user data using Gaussian distribution</li><li>Improve collaborative filtering to deal with dynamic user preferences</li><li>Use C++ libraries and APIs to manage model structures and parameters</li><li>Implement a C++ program to solve image classification tasks with LeNet architecture</li></ul><h4>Who this book is for</h4>You will find this C++ machine learning book useful if you want to get started with machine learning algorithms and techniques using the popular C++ language. As well as being a useful first course in machine learning with C++, this book will also appeal to data analysts, data scientists, and machine learning developers who are looking to implement different machine learning models in production using varied datasets and examples. Working knowledge of the C++ programming language is mandatory to get started with this book. |
| 538 ## - SYSTEM DETAILS NOTE | |
| System details note | Data in extended ASCII character set. |
| 538 ## - SYSTEM DETAILS NOTE | |
| System details note | Mode of access: Internet. |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | PACKT |
| 773 0# - HOST ITEM ENTRY | |
| Title | Hands-On Machine Learning with C++ |
| Place, publisher, and date of publication | GB,Packt,2020-05-15 |
| Physical description | 530 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | <a href="https://learning.packt.com/product/426615">https://learning.packt.com/product/426615</a> |
No items available.