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Natural language processing (NLP) has found its application in various domains, such as web search, advertisements, and customer services, and with the help of deep learning, we can enhance its performances in these areas.
This book teaches you how to leverage deep learning models for performing various NLP tasks, along with best practices in dealing with today's NLP challenges.
To begin with, you will understand the core concepts of NLP and deep learning, such as Convolutional Neural Networks (CNNs), recurrent neural networks (RNNs), semantic embedding, Word2vec, and more. You will learn how to perform each and every task of NLP using neural networks, in which you will train and deploy neural networks in your NLP applications.
By the end of this book, you will be well versed in building deep learning-backed NLP applications, along with overcoming NLP challenges with best practices developed by domain experts.
- Weave neural networks into linguistic applications across various platforms
- Perform NLP tasks and train its models using NLTK and TensorFlow
- Boost your NLP models with strong deep learning architectures such as CNNs and RNNs
- Rajesh Arumugam is an ML developer at SAP, Singapore.
- Rajalingappaa Shanmugamani is a deep learning lead at SAP, Singapore.
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