Shashidhar Soppin - Essentials of Deep Learning and AI: Experience Unsupervised Learning, Autoencoders, Feature Engineering, and Time Series Analysis with TensorFlow, Keras, and scikit-learn (English Edition)
Here you can read online Shashidhar Soppin - Essentials of Deep Learning and AI: Experience Unsupervised Learning, Autoencoders, Feature Engineering, and Time Series Analysis with TensorFlow, Keras, and scikit-learn (English Edition) full text of the book (entire story) in english for free. Download pdf and epub, get meaning, cover and reviews about this ebook. year: 2021, publisher: BPB Publications, genre: Children. Description of the work, (preface) as well as reviews are available. Best literature library LitArk.com created for fans of good reading and offers a wide selection of genres:
Romance novel
Science fiction
Adventure
Detective
Science
History
Home and family
Prose
Art
Politics
Computer
Non-fiction
Religion
Business
Children
Humor
Choose a favorite category and find really read worthwhile books. Enjoy immersion in the world of imagination, feel the emotions of the characters or learn something new for yourself, make an fascinating discovery.
- Book:Essentials of Deep Learning and AI: Experience Unsupervised Learning, Autoencoders, Feature Engineering, and Time Series Analysis with TensorFlow, Keras, and scikit-learn (English Edition)
- Author:
- Publisher:BPB Publications
- Genre:
- Year:2021
- Rating:4 / 5
- Favourites:Add to favourites
- Your mark:
Essentials of Deep Learning and AI: Experience Unsupervised Learning, Autoencoders, Feature Engineering, and Time Series Analysis with TensorFlow, Keras, and scikit-learn (English Edition): summary, description and annotation
We offer to read an annotation, description, summary or preface (depends on what the author of the book "Essentials of Deep Learning and AI: Experience Unsupervised Learning, Autoencoders, Feature Engineering, and Time Series Analysis with TensorFlow, Keras, and scikit-learn (English Edition)" wrote himself). If you haven't found the necessary information about the book — write in the comments, we will try to find it.
Drives next generation path with latest design techniques and methods in the fields of AI and Deep Learning
Key Features
Extensive examples of Machine Learning and Deep Learning principles.
Includes graphical demonstrations and visual tutorials for various libraries, configurations, and settings.
Numerous use cases with the code snippets and examples are presented.
Description
Essentials of Deep Learning and AI curates the essential knowledge of working on deep neural network techniques and advanced machine learning concepts. This book is for those who want to know more about how deep neural networks work and advanced machine learning principles including real-world examples.
This book includes implemented code snippets and step-by-step instructions for how to use them. Youll be amazed at how SciKit-Learn, Keras, and TensorFlow are used in AI applications to speed up the learning process and produce superior results. With the help of detailed examples and code templates, youll be running your scripts in no time. You will practice constructing models and optimise performance while working in an AI environment.
Readers will be able to start writing their programmes with confidence and ease. Experts and newcomers alike will have access to advanced methodologies. For easier reading, concept explanations are presented straightforwardly, with all relevant facts included.
What you will learn
Learn feature engineering using a variety of autoencoders, CNNs, and LSTMs.
Get to explore Time Series, Computer Vision and NLP models with insightful examples.
Dive deeper into Activation and Loss functions with various scenarios.
Get the experience of Deep Learning and AI across IoT, Telecom, and Health Care.
Build a strong foundation around AI, ML and Deep Learning principles and key concepts.
Who this book is for
This book targets Machine Learning Engineers, Data Scientists, Data Engineers, Business Intelligence Analysts, and Software Developers who wish to gain a firm grasp on the fundamentals of Deep Learning and Artificial Intelligence. Readers should have a working knowledge of computer programming concepts.
Table of Contents
1. Introduction
2. Supervised Machine Learning
3. System Analysis with Machine Learning/Un-Supervised Learning
4. Feature Engineering
5. Classification, Clustering, Association Rules, and Regression
6. Time Series Analysis
7. Data Cleanup, Characteristics and Feature Selection
8. Ensemble Model Development
9. Design with Deep Learning
10. Design with Multi Layered Perceptron (MLP)
11. Long Short Term Memory Networks
12. Autoencoders
13. Applications of Machine Learning and Deep Learning
14. Emerging and Future Technologies.
Shashidhar Soppin: author's other books
Who wrote Essentials of Deep Learning and AI: Experience Unsupervised Learning, Autoencoders, Feature Engineering, and Time Series Analysis with TensorFlow, Keras, and scikit-learn (English Edition)? Find out the surname, the name of the author of the book and a list of all author's works by series.
Essentials of Deep Learning and AI: Experience Unsupervised Learning, Autoencoders, Feature Engineering, and Time Series Analysis with TensorFlow, Keras, and scikit-learn (English Edition) — read online for free the complete book (whole text) full work
Below is the text of the book, divided by pages. System saving the place of the last page read, allows you to conveniently read the book "Essentials of Deep Learning and AI: Experience Unsupervised Learning, Autoencoders, Feature Engineering, and Time Series Analysis with TensorFlow, Keras, and scikit-learn (English Edition)" online for free, without having to search again every time where you left off. Put a bookmark, and you can go to the page where you finished reading at any time.
Font size:
Interval:
Bookmark:
Deep Learning and
AI
Autoencoders, Feature Engineering and
Time Series Analysis with TensorFlow,
Keras, and scikit-learn
www.bpbonline.com
FIRST EDITION 2022
Copyright BPB Publications, India
ISBN: 978-93-91030-353
All Rights Reserved. No part of this publication may be reproduced, distributed or transmitted in any form or by any means or stored in a database or retrieval system, without the prior written permission of the publisher with the exception to the program listings which may be entered, stored and executed in a computer system, but they can not be reproduced by the means of publication, photocopy, recording, or by any electronic and mechanical means.
LIMITS OF LIABILITY AND DISCLAIMER OF WARRANTY
The information contained in this book is true to correct and the best of authors and publishers knowledge. The author has made every effort to ensure the accuracy of these publications, but publisher cannot be held responsible for any loss or damage arising from any information in this book.
All trademarks referred to in the book are acknowledged as properties of their respective owners but BPB Publications cannot guarantee the accuracy of this information.
www.bpbonline.com
Machine learning (ML) and artificial intelligence (AI) are revolutionizing almost every aspect of the business. From self-driven cars to predicting inventory to diagnosing cancer, AI is set to impact nearly every domain and industry vertical.
While it is evident that AI is the most important technology of our times, there is not enough talent in the market. It is partly due to the complexity involved in learning and mastering the concepts of ML and AI. Many budding professionals and existing software developers aspiring to become AI engineers are often overwhelmed by the breadth and depth of the available tools and technologies.
This book, Essentials of Deep Learning and AI, by Shashidhar Soppin, Dr. Manjunath Ramachandra, and B N Chandrashekar, takes a unique approach in introducing the fundamental concepts of AI and ML. It will appeal to novices and experienced ML engineers due to the breadth and depth of the topics covered. Its one of the most comprehensive books on AI available in the market.
What I like about this book is the balance it strikes between the theoretical and practical aspects of AI. It doesnt intimidate those whose background is not mathematics or statistics. It also has the right balance between classical machine learning and deep learning, current and emerging techniques of AI. It is relevant to developers, business managers, technology decision-makers, and IT leaders.
The book has all the attributes to become an authoritative guide or textbook for teaching and learning ML and AI. Each chapter has a summary that acts as a quick reference. The multiple-choice questions at the end of each chapter enable the readers to assess themselves.
If you want to learn everything from the evolution of AI to advanced concepts such as ensemble methods and model optimization, look no further. This book has it all.
Mr Janakiram MSV
All the "Covid Warriors" who fought the war against the pandemic and A big thank you to all the corona warriors for all the selfless service offered.
Shashidhar Soppin has two decades of experience in IT industry. At present he is working as Enterprise Architect in Zeta. Earlier, he has worked as DMTS (Distinguished Member of Technical Staff) with progressive history of defining vision, strategy, and technical roadmap, architecting solutions, recommending new approaches via technology enablement and managing large-scale & complex IT projects as part of Wipro. He has worked on, Multi-Cloud (OpenStack, Azure/AWS), Cloud Native Technologies, AIX-OS, HCI (Hyper Converged Infra), Docker Containers and Kubernetes for microservices-based architectures and in Virtualization domains. His areas of interest include AI/ML, Deep Learning and IoT. He has several granted and filed patents on various technologies on his name. He is an avid Author for the OSFY Magazine, Written Articles on Micro-services and Kubernetes, Docker, OpenStack, Storage, Node Red, ML & DL to name few {https://opensourceforu.com/author/shashidharsoppin/}. He has also written articles for Medium.com and Research-gate and also a blogger for Linux-techi. He has presented papers in conferences and panel speaker in industry forums. He has worked for various organizations including IBM-ISL, Ness Technologies before joining Wipro. He got certified from Great Learning Institute on Deep Learning Technology, Deep Learning Specialization from Coursera and has various Cloud certifications.
linkedin.com/in/shashidhar-soppin-8264282
https://www.linuxtechi.com/author/shashidhar/
Dr. Manjunath Ramachandra has a blend of experience over twenty five years in the verticals of Healthcare, Telecom and consumer electronics spanning the technologies such as signal & Image processing, Artificial intelligence, cloud computing, IoT, wireless communication and quantum computing. He worked for the companies such as Tata Consultancy Services, Royal Philips and was placed in Wipro Limited as principal consultant. He has filed about 90 patents, authored 210 Research papers in international conferences and journals and a book. He was a member of the embedded systems special interest group at NASSCOM. He represented the industry in international standardization bodies such as Wi-Fi Alliance, served as the editor for the regional profiles standard in Digital living network alliance (DLNA) and as the industry liaison officer for the CE-Linux Forum. He has delivered over 24 keynote speeches and conducted over 21 workshop and tutorial sessions. He figures in Marquis Whos Who 2008 & 2000 outstanding intellectuals of the 21st century, International Biographical Center, UK. His areas of interest include Deep Learning/ Artificial intelligence, Signal & Image processing and wireless communications.
B N Chandrashekar, a principal consultant by designation is a veteran of Wipro Technologies Limited and has industry experience of around 20 years. He is a post graduate from Indian Institute of Science and has toned his credibility by owning and getting moulded in the roles of Researcher, Data Science Consultant, Technical Director and Full Stack AI Consultant. He has handled multiple cross-domain projects starting from infrastructure setup to scoping, development, delivery and with support and maintenance. He has work experience in cutting edge technologies and adapts to any new technology in a short time. He has experience in writing proposals, hands-on in multiple high-level programming and scripting languages. He has contributed to programs and tools to open source, co-authored journals and conference papers. He has co-authored publications to online portals like
Font size:
Interval:
Bookmark:
Similar books «Essentials of Deep Learning and AI: Experience Unsupervised Learning, Autoencoders, Feature Engineering, and Time Series Analysis with TensorFlow, Keras, and scikit-learn (English Edition)»
Look at similar books to Essentials of Deep Learning and AI: Experience Unsupervised Learning, Autoencoders, Feature Engineering, and Time Series Analysis with TensorFlow, Keras, and scikit-learn (English Edition). We have selected literature similar in name and meaning in the hope of providing readers with more options to find new, interesting, not yet read works.
Discussion, reviews of the book Essentials of Deep Learning and AI: Experience Unsupervised Learning, Autoencoders, Feature Engineering, and Time Series Analysis with TensorFlow, Keras, and scikit-learn (English Edition) and just readers' own opinions. Leave your comments, write what you think about the work, its meaning or the main characters. Specify what exactly you liked and what you didn't like, and why you think so.