Python Programming Handbook For Natural Language Processing: A Complete Beginners Guide To Building Chatbots Analyze Sentiments and Extract Meaning From … and TensorFlow (The Python Power Toolkit)
by Hazel Mackay
English | March 29, 2024 | ASIN: B0CZJ32YZ5 | 164 pages | PDF | 57 Mb
by Hazel Mackay
English | March 29, 2024 | ASIN: B0CZJ32YZ5 | 164 pages | PDF | 57 Mb
Unleash the Power of Language with Python: Your Comprehensive Guide to Natural Language Processing
Python Programming Handbook for Natural Language Processing equips you with the practical know-how to build intelligent language applications. This book is your roadmap to mastering Natural Language Processing (NLP), a cutting-edge field that lets computers understand and manipulate human language.
Whether you're a programmer looking to enhance your skillset or a curious learner fascinated by the science behind language, this handbook is your gateway to this revolutionary field.
Here's what sets this book apart:
- Gradual Learning Curve: We'll begin with the fundamentals of Python programming, making this perfect for beginners who are new to coding. We'll then seamlessly transition into core NLP concepts like tokenization, stemming, and part-of-speech tagging.
- Hands-on Exercises: Forget dry theory! This book is packed with engaging exercises that solidify your understanding. You'll learn by doing, implementing NLP techniques on real-world datasets to solve practical problems.
- Master Powerful Libraries: Dive deep into popular NLP libraries like NLTK, spaCy, and Gensim. You'll gain the expertise to leverage these powerful tools for tasks like sentiment analysis, topic modeling, and text summarization.
- Modern Deep Learning Approaches: Explore the frontiers of NLP with in-depth coverage of deep learning architectures like recurrent neural networks (RNNs) and transformers. You'll be able to build advanced applications for tasks such as machine translation and text generation.
- Comprehensive Coverage: This book is your one-stop shop for everything NLP! It covers a wide range of topics, from text preprocessing and information retrieval to dialogue systems and chatbots.
- Clean and prepare text data for NLP applications.
- Extract meaning from text using techniques like sentiment analysis and topic modeling.
- Build intelligent systems that can respond to natural language queries.
- Leverage deep learning models to perform advanced NLP tasks.
- Develop innovative language applications to solve real-world problems.