Description: Further DetailsTitle: Mastering NLP from Foundations to LLMsCondition: NewFormat: PaperbackEAN: 9781804619186Language: EnglishISBN-10: 1804619183ISBN: 9781804619186Author: Meysam Ghaffari, Lior GazitItem Length: 191mmItem Height: 235mmType: AI & Machine LearningSubtitle: Apply advanced rule-based techniques to LLMs and solve real-world business problems using PythonPublisher: Packt Publishing LimitedRelease Date: 04/26/2024Description: Enhance your NLP proficiency with modern frameworks like LangChain, explore mathematical foundations and code samples, and gain expert insights into current and future trends Key FeaturesLearn how to build Python-driven solutions with a focus on NLP, LLMs, RAGs, and GPTMaster embedding techniques and machine learning principles for real-world applicationsUnderstand the mathematical foundations of NLP and deep learning designsPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionDo you want to master Natural Language Processing (NLP) but don’t know where to begin? This book will give you the right head start. Written by leaders in machine learning and NLP, Mastering NLP from Foundations to LLMs provides an in-depth introduction to techniques. Starting with the mathematical foundations of machine learning (ML), you’ll gradually progress to advanced NLP applications such as large language models (LLMs) and AI applications. You’ll get to grips with linear algebra, optimization, probability, and statistics, which are essential for understanding and implementing machine learning and NLP algorithms. You’ll also explore general machine learning techniques and find out how they relate to NLP. Next, you’ll learn how to preprocess text data, explore methods for cleaning and preparing text for analysis, and understand how to do text classification. You’ll get all of this and more along with complete Python code samples.By the end of the book, the advanced topics of LLMs’ theory, design, and applications will be discussed along with the future trends in NLP, which will feature expert opinions. You’ll also get to strengthen your practical skills by working on sample real-world NLP business problems and solutions.What you will learnMaster the mathematical foundations of machine learning and NLP Implement advanced techniques for preprocessing text data and analysis Design ML-NLP systems in PythonModel and classify text using traditional machine learning and deep learning methodsUnderstand the theory and design of LLMs and their implementation for various applications in AIExplore NLP insights, trends, and expert opinions on its future direction and potentialWho this book is forThis book is for deep learning and machine learning researchers, NLP practitioners, ML/NLP educators, and STEM students. Professionals working with text data as part of their projects will also find plenty of useful information in this book. Beginner-level familiarity with machine learning and a basic working knowledge of Python will help you get the best out of this book.Country/Region of Manufacture: GBContributor: Asha Saxena (Foreword by)Genre: Computing & InternetRelease Year: 2024 Missing Information?Please contact us if any details are missing and where possible we will add the information to our listing.
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Book Title: Mastering NLP from Foundations to LLMs
Title: Mastering NLP from Foundations to LLMs
EAN: 9781804619186
ISBN-10: 1804619183
ISBN: 9781804619186
Item Height: 235mm
Subtitle: Apply advanced rule-based techniques to LLMs and solve real-world
Release Date: 04/26/2024
Release Year: 2024
Country/Region of Manufacture: GB
Contributor: Asha Saxena (Foreword by)
Genre: Computing & Internet
Publication Name: Mastering NLP from Foundations to LLMs : Apply Advanced Rule-Based Techniques to LLMs and Solve Real-world Business Problems Using Python
Language: English
Publisher: Packt Publishing, The Limited
Subject: Natural Language Processing
Publication Year: 2024
Type: Textbook
Subject Area: Computers
Author: Lior Gazit, Meysam Ghaffari
Item Length: 92.5 in
Item Width: 75 in
Format: Trade Paperback
