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Hands-On Natural Language Processing with Python. A practical guide to applying deep learning architectures to your NLP applications

(ebook) (audiobook) (audiobook) Książka w języku 1
Hands-On Natural Language Processing with Python. A practical guide to applying deep learning architectures to your NLP applications Rajesh Arumugam, Rajalingappaa Shanmugamani, Auguste Byiringiro, Chaitanya Joshi, Karthik Muthuswamy - okladka książki

Hands-On Natural Language Processing with Python. A practical guide to applying deep learning architectures to your NLP applications Rajesh Arumugam, Rajalingappaa Shanmugamani, Auguste Byiringiro, Chaitanya Joshi, Karthik Muthuswamy - okladka książki

Hands-On Natural Language Processing with Python. A practical guide to applying deep learning architectures to your NLP applications Rajesh Arumugam, Rajalingappaa Shanmugamani, Auguste Byiringiro, Chaitanya Joshi, Karthik Muthuswamy - audiobook MP3

Hands-On Natural Language Processing with Python. A practical guide to applying deep learning architectures to your NLP applications Rajesh Arumugam, Rajalingappaa Shanmugamani, Auguste Byiringiro, Chaitanya Joshi, Karthik Muthuswamy - audiobook CD

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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. Hands-On Natural Language Processing with Python 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. You will get accustomed to using RNNs and CNNs in various application areas, such as text classification and sequence labeling, which are essential in the application of sentiment analysis, customer service chatbots, and anomaly detection. You will be equipped with practical knowledge in order to implement deep learning in your linguistic applications using Python's popular deep learning library, TensorFlow.

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.

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O autorach książki

Rajesh Arumugam is an ML developer at SAP, Singapore. Previously, he developed ML solutions for smart city development in areas such as passenger flow analysis in public transit systems and optimization of energy consumption in buildings when working with Centre for Social Innovation at Hitachi Asia, Singapore. He has published papers in conferences and has pending patents in storage and ML. He holds a PhD in computer engineering from Nanyang Technological University, Singapore.
Rajalingappaa Shanmugamani is currently working as an Engineering Manager for a Deep learning team at Kairos. Previously, he worked as a Senior Machine Learning Developer at SAP, Singapore and worked at various startups in developing machine learning products. He has a Masters from Indian Institute of TechnologyMadras. He has published articles in peer-reviewed journals and conferences and submitted applications for several patents in the area of machine learning. In his spare time, he coaches programming and machine learning to school students and engineers.

Rajesh Arumugam, Rajalingappaa Shanmugamani, Auguste Byiringiro, Chaitanya Joshi, Karthik Muthuswamy - pozostałe książki

Packt Publishing - inne książki

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