NLU Meghalaya Library

Online Public Access Catalogue (OPAC)

Python Machine Learning By Example. (Record no. 14289)

MARC details
000 -LEADER
fixed length control field 03422nam a2200265uu 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20250616150220.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
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024 80 - OTHER STANDARD IDENTIFIER
Standard number or code 9781835082225
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 Yuxi (Hayden) Liu
Relator term author.
245 00 - TITLE STATEMENT
Title Python Machine Learning By Example.
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. GB:
Name of publisher, distributor, etc. Packt,
Date of publication, distribution, etc. 2024-07-31.
263 ## - PROJECTED PUBLICATION DATE
Projected publication date 2024-07-31
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 518.
377 ## - ASSOCIATED LANGUAGE
Language code en
520 ## - SUMMARY, ETC.
Summary, etc. <p><b>Author Yuxi (Hayden) Liu teaches machine learning from the fundamentals to building NLP transformers and multimodal models with best practice tips and real-world examples using PyTorch, TensorFlow, scikit-learn, and pandas</b></p><h4>Key Features</h4><ul><li>Discover new and updated content on NLP transformers, PyTorch, and computer vision modeling</li><li>Includes a dedicated chapter on best practices and additional best practice tips throughout the book to improve your ML solutions</li><li>Implement ML models, such as neural networks and linear and logistic regression, from scratch</li><li>Purchase of the print or Kindle book includes a free PDF copy</li></ul><h4>Book Description</h4>The fourth edition of Python Machine Learning By Example is a comprehensive guide for beginners and experienced machine learning practitioners who want to learn more advanced techniques, such as multimodal modeling. Written by experienced machine learning author and ex-Google machine learning engineer Yuxi (Hayden) Liu, this edition emphasizes best practices, providing invaluable insights for machine learning engineers, data scientists, and analysts.<br/><br/>Explore advanced techniques, including two new chapters on natural language processing transformers with BERT and GPT, and multimodal computer vision models with PyTorch and Hugging Face. You’ll learn key modeling techniques using practical examples, such as predicting stock prices and creating an image search engine.<br/><br/>This hands-on machine learning book navigates through complex challenges, bridging the gap between theoretical understanding and practical application. Elevate your machine learning and deep learning expertise, tackle intricate problems, and unlock the potential of advanced techniques in machine learning with this authoritative guide.<h4>What you will learn</h4><ul><li>Follow machine learning best practices throughout data preparation and model development</li><li>Build and improve image classifiers using convolutional neural networks (CNNs) and transfer learning</li><li>Develop and fine-tune neural networks using TensorFlow and PyTorch</li><li>Analyze sequence data and make predictions using recurrent neural networks (RNNs), transformers, and CLIP</li><li>Build classifiers using support vector machines (SVMs) and boost performance with PCA</li><li>Avoid overfitting using regularization, feature selection, and more</li></ul><h4>Who this book is for</h4>This expanded fourth edition is ideal for data scientists, ML engineers, analysts, and students with Python programming knowledge. The real-world examples, best practices, and code prepare anyone undertaking their first serious ML project.
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 Python Machine Learning By Example
Place, publisher, and date of publication GB,Packt,2024-07-31
Physical description 518
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://learning.packt.com/product/475677">https://learning.packt.com/product/475677</a>

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