Afbeelding 1 van 9
Galerij
Afbeelding 1 van 9
Hebt u iets om te verkopen?
Python Machine Learning By Example Fourth (4th) Edition By Liu Expert Insight
US $36,50
OngeveerEUR 31,15
Objectstaat:
Heel goed
Een boek dat er niet als nieuw uitziet en is gelezen, maar zich in uitstekende staat bevindt. De kaft is niet zichtbaar beschadigd en het eventuele stofomslag zit nog om de harde kaft heen. Er ontbreken geen bladzijden en er zijn geen bladzijden beschadigd. Er is geen tekst onderstreept of gemarkeerd en er is niet in de kantlijn geschreven. Er kunnen zeer minimale identificatiemerken aan de binnenzijde van de kaft zijn aangebracht. De slijtage is zeer minimaal. Bekijk de aanbieding van de verkoper voor de volledige details en een beschrijving van gebreken.
- Nu kopenPython Machine Learning By Example Fourth (4th) Edition By Liu Expert Insight
Oops! Looks like we're having trouble connecting to our server.
Refresh your browser window to try again.
Verzendkosten:
US $5,97 (ongeveer EUR 5,09) USPS Media MailTM.
Bevindt zich in: Las Vegas, Nevada, Verenigde Staten
Levering:
Geschatte levering tussen wo, 27 aug en vr, 29 aug tot 94104
Retourbeleid:
Geen retourzendingen geaccepteerd.
Betalingen:
Winkel met vertrouwen
De verkoper neemt de volledige verantwoordelijkheid voor deze aanbieding.
eBay-objectnummer:205399087497
Specificaties
- Objectstaat
- Brand
- Packt Publishing
- Binding
- TP
- EAN
- 9781835085622
- ISBN
- 1835085628
- Book Title
- Python Machine Learning By Example - Fourth Editio
- Item Height
- 1.04
- Manufacturer
- Packt Publishing
- Item Weight
- 1.94
Over dit product
Product Identifiers
Publisher
Packt Publishing, The Limited
ISBN-10
1835085628
ISBN-13
9781835085622
eBay Product ID (ePID)
14069428426
Product Key Features
Number of Pages
Xxiii, 491 Pages
Language
English
Publication Name
Python Machine Learning by Example : Unlock Machine Learning Best Practices with Real-World Use Cases
Subject
Machine Theory, Software Development & Engineering / Tools, Mathematical & Statistical Software, General
Publication Year
2024
Type
Textbook
Subject Area
Computers, Science
Format
Trade Paperback
Dimensions
Item Length
92.5 in
Item Width
75 in
Additional Product Features
Intended Audience
Trade
Dewey Edition
23
Illustrated
Yes
Dewey Decimal
006.31
Synopsis
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.Get With Your Book: PDF Copy, AI Assistant, and Next-Gen Reader Free Key Features Discover new and updated content on NLP transformers, PyTorch, and computer vision modeling Includes a dedicated chapter on best practices and additional best practice tips throughout the book to improve your ML solutions Implement ML models, such as neural networks and linear and logistic regression, from scratch Book Description 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.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.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. What you will learn Follow machine learning best practices throughout data preparation and model development Build and improve image classifiers using convolutional neural networks (CNNs) and transfer learning Develop and fine-tune neural networks using TensorFlow and PyTorch Analyze sequence data and make predictions using recurrent neural networks (RNNs), transformers, and CLIP Build classifiers using support vector machines (SVMs) and boost performance with PCA Avoid overfitting using regularization, feature selection, and more Who this book is for 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. ]]>, 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 Key Features: - Discover new and updated content on NLP transformers, PyTorch, and computer vision modeling - Includes a dedicated chapter on best practices and additional best practice tips throughout the book to improve your ML solutions - Implement ML models, such as neural networks and linear and logistic regression, from scratch - Purchase of the print or Kindle book includes a free PDF copy Book Description: The fourth edition of Python Machine Learning by Example is a comprehensive guide for beginners and experienced ML practitioners who want to learn more advanced techniques like multimodal modeling. Written by experienced machine learning author and ex-Google ML engineer Yuxi (Hayden) Liu, this edition emphasizes best practices, providing invaluable insights for ML engineers, data scientists, and analysts. 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. 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. What You Will Learn: - Follow machine learning best practices across data preparation and model development - Build and improve image classifiers using Convolutional Neural Networks (CNNs) and transfer learning - Develop and fine-tune neural networks using TensorFlow and PyTorch - Analyze sequence data and make predictions using RNNs, transformers, and CLIP - Build classifiers using SVMs and boost performance with PCA - Avoid overfitting using regularization, feature selection, and more Who this book is for: 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. Table of Contents - Getting Started with Machine Learning and Python - Building a Movie Recommendation Engine - Predicting Online Ad Click-Through with Tree-Based Algorithms - Predicting Online Ad Click-Through with Logistic Regression - Predicting Stock Prices with Regression Algorithms - Predicting Stock Prices with Artificial Neural Networks - Mining the 20 Newsgroups Dataset with Text Analysis Techniques - Discovering Underlying Topics in the Newsgroups Dataset with Clustering and Topic Modeling - Recognizing Faces with Support Vector Machine - Machine Learning Best Practices - Categorizing Images of Clothing with Convolutional Neural Networks - Making Predictions with Sequences Using Recurrent Neural Networks - Advancing Language Understanding and Generation with Transformer Models - Building An Image Search Engine Using Multimodal Models - Making Decisions in Complex Environments with Reinforcement Learning
LC Classification Number
Q325.5.L5 2024
Objectbeschrijving van de verkoper
Over deze verkoper
topnvdeals
100% positieve feedback•4,9K objecten verkocht
Geregistreerd als particuliere verkoperDus de consumentenrechten die voortvloeien uit EU-wetgeving voor consumentenbescherming zijn niet van toepassing. eBay-kopersbescherming geldt nog steeds voor de meeste aankopen.
Feedback verkoper (1.300)
- l***s (906)- Feedback gegeven door koper.Afgelopen maandGeverifieerde aankoopAce
- y***n (293)- Feedback gegeven door koper.Afgelopen maandGeverifieerde aankoopThank you was perfect and shipping was super fast AAA+++
- r***o (1)- Feedback gegeven door koper.Afgelopen maandGeverifieerde aankoopIt was a great purchase meet expectations of good quality great condition
topnvdeals
100% positieve feedback•4,9K objecten verkocht
Geregistreerd als particuliere verkoperDus de consumentenrechten die voortvloeien uit EU-wetgeving voor consumentenbescherming zijn niet van toepassing. eBay-kopersbescherming geldt nog steeds voor de meeste aankopen.
Feedback verkoper (1.300)
- l***s (906)- Feedback gegeven door koper.Afgelopen maandGeverifieerde aankoopAce
- y***n (293)- Feedback gegeven door koper.Afgelopen maandGeverifieerde aankoopThank you was perfect and shipping was super fast AAA+++
- r***o (1)- Feedback gegeven door koper.Afgelopen maandGeverifieerde aankoopIt was a great purchase meet expectations of good quality great condition