Natural Language Processing and Machine Learning for Developers (eBook)

<p><b>Unlock the potential of NLP and machine learning with this comprehensive guide. Learn advanced techniques, implement practical applications, and master tools like NumPy, Pandas, and transformer models.</b></p><h4>Key Features</h4><ul><li>Comprehensive guide to NLP and machine learning</li><li>Practical examples and code samples</li><li>Covers from basic to advanced techniques and applications</li></ul><h4>Book Description</h4>This book introduces developers to basic concepts in NLP and machine learning, providing numerous code samples to support the topics covered. The journey begins with introductory material on NumPy and Pandas, essential for data manipulation. Following this, chapters delve into NLP concepts, algorithms, and toolkits, providing a solid foundation in natural language processing.<br />
As you progress, the book covers machine learning fundamentals and classifiers, demonstrating how these techniques are applied in NLP. Practical examples using TF2 and Keras illustrate how to implement various NLP tasks. Advanced topics include the Transformer architecture, BERT-based models, and the GPT family of models, showcasing the latest advancements in the field.<br />
The final chapters and appendices offer a comprehensive overview of related topics, including data and statistics, Python3, regular expressions, and data visualization with Matplotlib and Seaborn. Companion files with source code and figures ensure a hands-on learning experience. This book equips you with the knowledge and tools needed to excel in NLP and machine learning.<h4>What you will learn</h4><ul><li>Master NumPy and Pandas for data manipulation</li><li>Understand NLP concepts and techniques</li><li>Implement various NLP algorithms</li><li>Apply machine learning techniques</li><li>Use transformer models like BERT and GPT</li><li>Develop practical NLP applications</li></ul><h4>Who this book is for</h4><p>This book is ideal for developers and data scientists who want to enhance their skills in NLP and machine learning. Basic knowledge of Python is recommended. Prior experience with data manipulation and machine learning concepts is beneficial.</p>

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Unlock the potential of NLP and machine learning with this comprehensive guide. Learn advanced techniques, implement practical applications, and master tools like NumPy, Pandas, and transformer models.Key FeaturesComprehensive guide to NLP and machine learningPractical examples and code samplesCovers from basic to advanced techniques and applicationsBook DescriptionThis book introduces developers to basic concepts in NLP and machine learning, providing numerous code samples to support the topics covered. The journey begins with introductory material on NumPy and Pandas, essential for data manipulation. Following this, chapters delve into NLP concepts, algorithms, and toolkits, providing a solid foundation in natural language processing. As you progress, the book covers machine learning fundamentals and classifiers, demonstrating how these techniques are applied in NLP. Practical examples using TF2 and Keras illustrate how to implement various NLP tasks. Advanced topics include the Transformer architecture, BERT-based models, and the GPT family of models, showcasing the latest advancements in the field. The final chapters and appendices offer a comprehensive overview of related topics, including data and statistics, Python3, regular expressions, and data visualization with Matplotlib and Seaborn. Companion files with source code and figures ensure a hands-on learning experience. This book equips you with the knowledge and tools needed to excel in NLP and machine learning.What you will learnMaster NumPy and Pandas for data manipulationUnderstand NLP concepts and techniquesImplement various NLP algorithmsApply machine learning techniquesUse transformer models like BERT and GPTDevelop practical NLP applicationsWho this book is forThis book is ideal for developers and data scientists who want to enhance their skills in NLP and machine learning. Basic knowledge of Python is recommended. Prior experience with data manipulation and machine learning concepts is beneficial.]]>