click to
look inside
look inside
Look inside
Source code
Book Forum
Source code on GitHub
🎙️ Paul Azunre interviewed
Improving NLP Model Training Time and Efficiency
Getting Started with Baselines
Shallow Transfer Learning in NLP
🎙️ Interview with Paul Azunre
🎙️ Dr. Paul Azunre: Going Against the Grain
🎙️ Conversation with Paul Azunre
🎙️ Expert Interview ~ Dr. Paul Azunre ~ Natural Language Processing NLP
Deep Transfer Learning for NLP with Transformers
🎙️ #PeopleWhoInspire with Dr. Paul Azunre
🎙️ Paul Azunre: On Balancing Passion and Profession | Music and Machine Learning
Manning Early Access Program (MEAP)
Read chapters as they are written, get the finished eBook as soon as it’s ready, and receive the pBook long before it's in bookstores.
FREE
You can see any available part of this book for free.Click the table of contents to start reading.
placing your order...
Don't refresh or navigate away from the page.
Transfer Learning for Natural Language Processing (print book) added to cart
continue shopping
go to cart
Transfer Learning for Natural Language Processing (eBook) added to cart
continue shopping
go to cart
A complex topic is broken down into manageable pieces, while maintaining a good pace. The text is accompanied by replicable code examples throughout.
Look inside
Building and training deep learning models from scratch is costly, time-consuming, and requires massive amounts of data. To address this concern, cutting-edge transfer learning techniques enable you to start with pretrained models you can tweak to meet your exact needs. In Transfer Learning for Natural Language Processing, DARPA researcher Paul Azunre takes you hands-on with customizing these open source resources for your own NLP architectures. You’ll learn how to use transfer learning to deliver state-of-the-art results even when working with limited label data, all while saving on training time and computational costs.
about the technology
Transfer learning enables machine learning models to be initialized with existing prior knowledge. Initially pioneered in computer vision, transfer learning techniques have been revolutionising Natural Language Processing with big reductions in the training time and computation power needed for a model to start delivering results. Emerging pretrained language models such as ELMo and BERT have opened up new possibilities for NLP developers working in machine translation, semantic analysis, business analytics, and natural language generation.about the book
Transfer Learning for Natural Language Processing is a practical primer to transfer learning techniques capable of delivering huge improvements to your NLP models. Written by DARPA researcher Paul Azunre, this practical book gets you up to speed with the relevant ML concepts before diving into the cutting-edge advances that are defining the future of NLP. You’ll learn how to adapt existing state-of-the art models into real-world applications, including building a spam email classifier, a movie review sentiment analyzer, an automated fact checker, a question-answering system and a translation system for low-resource languages.what's inside
- Fine tuning pretrained models with new domain data
- Picking the right model to reduce resource usage
- Transfer learning for neural network architectures
- Foundations for exploring NLP academic literature
about the author
Paul Azunre holds a PhD in Computer Science from MIT and has served as a Principal Investigator on several DARPA research programs. He founded Algorine Inc., a Research Lab dedicated to advancing AI/ML and identifying scenarios where they can have a significant social impact. Paul also co-founded Ghana NLP, an open source initiative focused using NLP and Transfer Learning with Ghanaian and other low-resource languages. He frequently contributes to major peer-reviewed international research journals and serves as a program committee member at top conferences in the field.FREE domestic shipping on orders of three or more print books
Does a great job of introducing the reader to Transfer Learning for Natural Language Processing.
Guides you through different exercises with real case scenarios where you can feel your work is getting valuable and exciting at the same time.
An interesting book that introduces Transfer Learning techniques in the domain of NLP.
One of the best written books of its kind!
Get a deeper understanding of transfer learning in the context of NLP and learn stuff that works!
Excellently written, and easy to follow.
related titles
related titles
