Deep outlet sale Learning for NLP new arrival and Speech Recognition online sale

Deep outlet sale Learning for NLP new arrival and Speech Recognition online sale

Deep outlet sale Learning for NLP new arrival and Speech Recognition online sale
Deep outlet sale Learning for NLP new arrival and Speech Recognition online sale__left

Description

Product Description

This textbook explains Deep Learning Architecture, with applications to various NLP Tasks, including Document Classification, Machine Translation, Language Modeling, and Speech Recognition. With the widespread adoption of deep learning, natural language processing (NLP),and speech applications in many areas (including Finance, Healthcare, and Government) there is a growing need for one comprehensive resource that maps deep learning techniques to NLP and speech and provides insights  into  using  the  tools  and  libraries  for  real-world  applications.  Deep Learning for NLP and Speech Recognition explains recent deep learning methods applicable to NLP and speech, provides state-of-the-art approaches, and offers real-world case studies with code to provide hands-on experience.  


Many books focus on deep learning theory or deep learning for NLP-specific tasks while others are cookbooks for tools and libraries, but the constant flux of new algorithms, tools, frameworks, and libraries in a rapidly evolving landscape means that there are few available texts that offer the material in this book. 

The book is organized into three parts, aligning to different groups of readers and their expertise. The three parts are:

      Machine Learning, NLP, and Speech Introduction

The first part has three chapters that introduce readers to the fields of  NLP, speech recognition,  deep learning and machine learning with basic theory and hands-on case studies using Python-based tools and libraries.

      Deep Learning Basics

The five chapters in the second part introduce deep learning and various topics that are crucial for speech and text processing, including word embeddings, convolutional neural networks, recurrent neural networks and speech recognition basics. Theory, practical tips, state-of-the-art methods, experimentations and analysis in using the methods discussed in theory on real-world tasks.

      Advanced Deep Learning Techniques for Text and Speech

The third part has five chapters that discuss the latest and cutting-edge research in the areas of deep learning that intersect with NLP and speech. Topics including attention mechanisms, memory augmented networks, transfer learning, multi-task learning, domain adaptation, reinforcement learning, and end-to-end deep learning for speech recognition are covered using case studies. 

From the Back Cover

With the widespread adoption of deep learning, natural language processing (NLP),and speech applications in many areas (including Finance, Healthcare, and Government) there is a growing need for one comprehensive resource that maps deep learning techniques to NLP and speech and provides insights  into  using  the  tools  and  libraries  for  real-world  applications.  Deep Learning for NLP and Speech Recognition explains recent deep learning methods applicable to NLP and speech, provides state-of-the-art approaches, and offers real-world case studies with code to provide hands-on experience. 


The book is organized into three parts, aligning to different groups of readers and their expertise. The three parts are:

      Machine Learning, NLP, and Speech Introduction

The first part has  three chapters that introduce readers to the fields of  NLP, speech recognition,  deep learning and machine learning with basic theory and hands-on case studies using Python-based tools and libraries.

      Deep Learning Basics

The five chapters in the second part introduce deep learning and various topics that are crucial for speech and text processing, including word embeddings, convolutional neural networks, recurrent neural networks and speech recognition basics. Theory, practical tips, state-of-the-art methods, experimentations and analysis in using the methods discussed in theory on real-world tasks.

      Advanced Deep Learning Techniques for Text and Speech

The third part has  five chapters that discuss the latest and cutting-edge research in the areas of deep learning that intersect with NLP and speech. Topics including attention mechanisms, memory augmented networks, transfer learning, multi-task learning, domain adaptation, reinforcement learning, and end-to-end deep learning for speech recognition are covered using case studies. 

About the Author

Uday Kamath has more than 20 years of experience architecting and building analytics-based commercial solutions. He currently works as the Chief Analytics Officer at Digital Reasoning, one of the leading companies in AI for NLP and Speech Recognition, heading the Applied Machine Learning research group. Most recently, Uday served as the Chief Data Scientist at BAE Systems Applied Intelligence, building machine learning products and solutions for the financial industry, focused on fraud, compliance, and cybersecurity. Uday has previously authored many books on machine learning such as Machine Learning: End-to-End guide for Java developers: Data Analysis, Machine Learning, and Neural Networks simplified and Mastering Java Machine Learning: A Java developer''s guide to implementing machine learning and big data architectures. Uday has published many academic papers in different machine learning journals and conferences. Uday has a Ph.D. in Big Data Machine Learning and was one of the first in generalized scaling of machine learning algorithms using evolutionary computing.

John Liu spent the past 22 years managing quantitative research, portfolio management and data science teams. He is currently CEO of Intelluron Corporation, an emerging AI-as-a-service solution company. Most recently, John was head of data science and data strategy as VP at Digital Reasoning. Previously, he was CIO of Spartus Capital, a quantitative investment firm in New York. Prior to that, John held senior executive roles at Citigroup, where he oversaw the portfolio solutions group that advised institutional clients on quantitative investment and risk strategies; at the Indiana Public Employees pension, where he managed the $7B public equities portfolio; at Vanderbilt University, where he oversaw the $2B equity and alternative investment portfolios; and at BNP Paribas, where he managed the US index options and MSCI delta-one trading desks. He is known for his expertise in reinforcement learning applied to investment management and has authored numerous papers and book chapters on topics including natural language processing, representation learning, systemic risk, asset allocation, and EM theory. In 2016, John was named Nashville''s Data Scientist of the Year. He earned his B.S., M.S., and Ph.D. in electrical engineering from the University of Pennsylvania and is a CFA Charterholder.

James (Jimmy) Whitaker manages Applied Research at Digital Reasoning. He currently leads deep learning developments in speech analytics in the FinTech space, and has spent the last 4 years building machine learning applications for NLP, Speech Recognition, and Computer Vision. He received his masters in Computer Science from the University of Oxford, where he received a distinction for his application of machine learning in the field of Steganalysis after completing his undergraduate degrees in Electrical Engineering and Computer Science from Christian Brothers University. Prior to his work in deep learning, Jimmy worked as a concept engineer and risk manager for complex transportation initiatives.

Product information

Brief content visible, double tap to read full content.
Full content visible, double tap to read brief content.

Videos

Help others learn more about this product by uploading a video!
Upload video
Brief content visible, double tap to read full content.
Full content visible, double tap to read brief content.

Customers who bought this item also bought

Customer reviews

4.6 out of 54.6 out of 5
39 global ratings

Top reviews from the United States

Rabiraj Banerjee
4.0 out of 5 starsVerified Purchase
This book is great with minor errors
Reviewed in the United States on November 14, 2020
This book is great, because the authors have supported theory with code Snippets of PyTorch which really helps in understanding, but I found a bit of a problem in the BPTT Derivation, there they have not used the summation symbol while calculating the loss which is usually... See more
This book is great, because the authors have supported theory with code Snippets of PyTorch which really helps in understanding, but I found a bit of a problem in the BPTT Derivation, there they have not used the summation symbol while calculating the loss which is usually a scalar, I had to derive the whole BPTT on my own after some intense reading from a Stanford presentation to confirm whether I was right or wrong. Other than that this book is just great :)
One person found this helpful
Helpful
Report
Nishikant D.
5.0 out of 5 starsVerified Purchase
Best book on Deep Learning
Reviewed in the United States on July 13, 2019
I got an early copy of this highly rated author Dr. Uday Kamath of "Mastering Java Machine Learning." Having a good understanding of machine learning but not ventured into Deep Learning and NLP/Speech, this book gave me a good overview starting from basics and most... See more
I got an early copy of this highly rated author Dr. Uday Kamath of "Mastering Java Machine Learning." Having a good understanding of machine learning but not ventured into Deep Learning and NLP/Speech, this book gave me a good overview starting from basics and most importantly the case studies with a hands-on approach to algorithms, comparisons, validation, etc. is helpful for a practitioner like me.
2 people found this helpful
Helpful
Report
A. Boros
5.0 out of 5 starsVerified Purchase
Great book on latest NLP trends
Reviewed in the United States on May 12, 2021
This book is encyclopedic summary of all NLP deep learning and also contains a short but great summary of deep reinforcement learning.
One person found this helpful
Helpful
Report
Raj Pai
5.0 out of 5 starsVerified Purchase
Great book to revise fundamentals and get upto speed on latest technologies for NLP
Reviewed in the United States on July 8, 2019
I have done ML many years ago. This book really helped me brush up on my fundmanetals around how ML and deep learning work and then went deeper into the latest state of the art for NLP and Speech Recognition explains recent deep learning methods applicable to NLP and speech... See more
I have done ML many years ago. This book really helped me brush up on my fundmanetals around how ML and deep learning work and then went deeper into the latest state of the art for NLP and Speech Recognition explains recent deep learning methods applicable to NLP and speech with real-world case studies and relevant code and access for were to find libraries for a hands-on experience.
Loved the book and is helping me enormously in driving my teams to rethink through some of the work we are doing...
One person found this helpful
Helpful
Report
Sunil Bharitkar
5.0 out of 5 starsVerified Purchase
Nice!
Reviewed in the United States on October 25, 2019
Very nicely written book!
One person found this helpful
Helpful
Report
Charlie A
5.0 out of 5 stars
Very well written for anyone interested in NLP
Reviewed in the United States on September 10, 2019
Let me be very clear. I am not interested in leaving reviews unless I am firmly compelled to do so. This summer I was interested in NLP and knowing John Liu in the Nashville data science community, I thought I would give it a read. Now, as many of these books go, it is a... See more
Let me be very clear. I am not interested in leaving reviews unless I am firmly compelled to do so. This summer I was interested in NLP and knowing John Liu in the Nashville data science community, I thought I would give it a read. Now, as many of these books go, it is a comprehensive books that is not best read cover to cover. But instead, start with the beginning and then find the sections that are best suited for you.

This is a book that may be a little tough for the beginner, but it is very well written that even the novice will understand their chapters on machine learning and the basics of deep learning. I was very interested in learning more about recurrent and concurrent neural networks and this book did not disappoint. I do have some mathematics background, but even without this knowledge, I feel that I would have still understood the book.

Well done and thank you writing a book on this subject that will be interesting for a wide range of individuals. Its practical basis made it easy to follow and (believe it or not) a joy to read. This will be my reference for NLP and speech recognition.
2 people found this helpful
Helpful
Report
bookbug
5.0 out of 5 stars
A must read for NLP practitioners
Reviewed in the United States on June 25, 2019
A great resource for having the concept, theory and the use cases all in one place. Not only basic NLP concepts such as word embeddings, convolutional neural networks, and recurrent networks are well explained with NLP domain, but the case study covers many standard and... See more
A great resource for having the concept, theory and the use cases all in one place. Not only basic NLP concepts such as word embeddings, convolutional neural networks, and recurrent networks are well explained with NLP domain, but the case study covers many standard and advanced methods in each using Keras or PyTorch very well. There are very few books or resources that cover the advanced chapters such as the Attention & Memory Networks, Domain Adaptation, and Reinforcement learning in a comprehensive way with the case studies, so definitely a big plus! Highly recommend.
5 people found this helpful
Helpful
Report
Lindsey C.
5.0 out of 5 stars
If you want to know deep learning for NLP, get this text.
Reviewed in the United States on August 11, 2019
“Deep Learning for NLP and Speech Recognition” is a comprehensive text that walks the reader through a complex topic in a thoughtful and easily consumable way. Chapter 3 on “Text and Speech Basics” sets the stage for contextual understanding of natural language processing,... See more
“Deep Learning for NLP and Speech Recognition” is a comprehensive text that walks the reader through a complex topic in a thoughtful and easily consumable way. Chapter 3 on “Text and Speech Basics” sets the stage for contextual understanding of natural language processing, critical for the ability to apply algorithms effectively to speech data. The authors weave Python snippets of analysis and case studies throughout the text, making application of the methodologies easy for the learner. Over 13 chapters, the concepts build upon each other, and the reader walks away with a comprehensive study of NLP and several deep learning methodologies, which can be applied to non-NLP problems. I especially enjoyed section 7.6, as the authors deftly describe how to convert language data and word embeddings into inputs for a recurrent neural network. Extensive and thorough resource for both scientists with proficient knowledge of NLP and scientists just getting started.
2 people found this helpful
Helpful
Report

Top reviews from other countries

Ismael Ezequiel
5.0 out of 5 starsVerified Purchase
This book is the best one of deep learning / NLP / Speech recognition from 2019;
Reviewed in Brazil on October 24, 2019
THE BEST BOOK UPDATED (2019) FOR NLP/SPEECH RECOGNITION AND DEEP LEARNING; FOR ANYONE INTERESTED IN THE FIELD OF DEEP LEARNING AND NLP, I STRONGLY RECOMMEND THIS BOOK;
Report
See all reviews
Brief content visible, double tap to read full content.
Full content visible, double tap to read brief content.

Customers who viewed this item also viewed

Brief content visible, double tap to read full content.
Full content visible, double tap to read brief content.

What other items do customers buy after viewing this item?

Deep outlet sale Learning for NLP new arrival and Speech Recognition online sale

Deep outlet sale Learning for NLP new arrival and Speech Recognition online sale

Deep outlet sale Learning for NLP new arrival and Speech Recognition online sale

Deep outlet sale Learning for NLP new arrival and Speech Recognition online sale

Deep outlet sale Learning for NLP new arrival and Speech Recognition online sale

Deep outlet sale Learning for NLP new arrival and Speech Recognition online sale

Deep outlet sale Learning for NLP new arrival and Speech Recognition online sale

Deep outlet sale Learning for NLP new arrival and Speech Recognition online sale

Deep outlet sale Learning for NLP new arrival and Speech Recognition online sale

Deep outlet sale Learning for NLP new arrival and Speech Recognition online sale

Deep outlet sale Learning for NLP new arrival and Speech Recognition online sale

Deep outlet sale Learning for NLP new arrival and Speech Recognition online sale

Deep outlet sale Learning for NLP new arrival and Speech Recognition online sale

Deep outlet sale Learning for NLP new arrival and Speech Recognition online sale