February 2021
Intermediate to advanced
380 pages
9h 5m
English
Overview
Delve into the advanced aspects of Natural Language Processing (NLP) with TensorFlow 2 through this comprehensive guide. "Advanced Natural Language Processing with TensorFlow 2" introduces cutting-edge methodologies like RNNs, Transformers, and sequence-to-sequence modeling to help you implement practical applications such as text summarization, dialogue systems, and more.
What this Book will help me do
- Develop advanced capabilities for NLP preprocessing tasks including tokenization and POS tagging.
- Apply Transformer architectures like GPT or BERT for text generation and sentiment analysis.
- Design and implement models for named entity recognition and text summarization.
- Integrate multimodal systems that combine image and text data for captions or Q&A.
- Adapt the included codebase to refine transfer learning workflows and improve custom models.
Author(s)
The book is authored by Ashish Bansal and None Mullen, who bring years of expertise in machine learning and NLP. Ashish Bansal has worked extensively on deep learning methodologies and has a knack for developing practical solutions for complex problems. None Mullen brings a wealth of teaching and professional experience, emphasizing clear explanations and hands-on applications.
Who is it for?
Designed for intermediate and advanced practitioners, this book is ideal for data scientists and machine learning developers wishing to elevate their NLP capabilities. Some proficiency with Python, machine learning concepts, and TensorFlow is assumed to best engage with the material. If you're seeking to implement advanced NLP techniques in real-world projects, this guide is tailored for you.
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