Artificial Intelligence and Deep Learning for Decision Makers

Kaur Dr. Jagreet

Description

Learn modern-day technologies from modern-day technical giants.KEY FEATURES1. Real-world success and failure stories of artificial intelligence explained2. Understand concepts of artificial intelligence and deep learning methods 3. Learn how to use artificial intelligence and deep learning methods4. Know how to prepare dataset and implement models using industry leading Python packages 5. You'll be able to apply and analyze the results produced by the models for predictionDESCRIPTION The aim of this book is to help the readers understand the concept of artificial intelligence and deep learning methods and implement them into their businesses and organizations. The first two chapters describe the introduction of the artificial intelligence and deep learning methods. In the first chapter, the concept of human thinking process, starting from the biochemical responses within the structure of neurons to the problem-solving steps through computational thinking skills are discussed. All chapters after the first two should be considered as the study of different technological and Artificial Intelligence giants of current age. These chapters are placed in a way that each chapter could be considered a separate study of a separate company, which includes the achievements of intelligent services currently provided by the company, discussion on the business model of the company towards the use of the deep learning technologies, the advancement of the web services which are incorporated with intelligent capability introduced by company, the efforts of the company in contributing to the development of the artificial intelligence and deep learning research. WHAT WILL YOU LEARN How to use the algorithms written in the Python programming language to design models and perform predictions in general datasetsUnderstand use cases in different industries related to the implementation of artificial intelligence and deep learning methodsLearn the use of potential ideas in artificial intelligence and deep learning methods to improve the operational processes or new products and how services can be produced based on the methodsWHO THIS BOOK IS FORThis book is targeted to business and organization leaders, technology enthusiasts, professionals, and managers who seek knowledge of artificial intelligence and deep learning methods.Table of Contents1. Artificial Intelligence and Deep Learning2. Data Science for Business Analysis3. Decision Making4. Intelligent Computing Strategies By Google 5. Cognitive Learning Services in IBM Watson6. Advancement web services by Baidu 7. Improved Social Business by Facebook8. Personalized Intelligent Computing by Apple9. Cloud Computing Intelligent by MicrosoftAbout the AuthorDr. Jagreet KaurDr. Jagreet Kaur is a doctorate in computer science and engineering. Her topic of thesis was "ARTIFICIAL INTELLIGENCE BASED ANALYTICAL PLATFORM FOR PREDICTIVE ANALYSIS IN HEALTH CARE." With more than 12 years of experience in academics and research, she is working in data wrangling, machine learning and deeplearning algorithms on large datasets, real-time data often in production environments for data science solutions and data products to get actionable insights for the last four years. She also possesses ten international publications and five national publications under her name.Her skill set includes data engineering skills (Hadoop, Apache Spark, Apache Kafka, Cassandra, Hive, Flume, Scoop, and Elasticsearch), programming skills (Python, Angularjs, D3.js , Machine Learning, and R), data science skills (Statistics, Machine Learning, NLP, NLTK, Artificial Intelligence, R, Python, Pandas, Sklearn, Hadoop, SQL, Statistical Modeling, Data Munging, Decision Science, Machine Learning, Graph Analysis, Text Mining and Optimization, and Web Scraping, Deep learning packages:- Theano, Keras, Tensorflow, Pytorch, Julia) and Algorithms Specialization (Regression Algorithms: Linear Regression, Random Forest Regressor, XGBoost, SVR, Ridge Regression, Lasso Regression, Neural Networks Classification Algorithms: Decision Trees, Random Forest Classifier, Support Vector Machines(SVM), Logistic Regression, KNN Classifier, Neural Network, Clustering Algorithms: K-Means, DBSCAN, Deep Learning Algorithms: Simple RNN, LSTM Network, GRU)Currently, she works as a Chief Operating Officer (COO) and Chief Data Scientist in Xenonstack. Under her Guidance, more than 400 projects are already developed and productionized which also includes more than 200 AI and data science projects. Navdeep Singh GillNaveed Singh Gill is a technology and solution architect having more than 15 years of experience in the IT and Telecom industry. For the past six years, he is working in big data analytics, automation and advanced analytics using machine learning and deep learning for planning and architecting of data science solutions and data products. He's also working in 3 As (Analytics, Automation, and AI), more focused on writing software for building data lake, analytics platform , NoSQL deployments, data migration, data modelling tasks, ML/DL on real-time data often in production environments.He started his career with HFCL Infotel as a network engineer for managing the technical network of Broadband Customers with Linux servers and Cisco routers. He also worked in Ericsson, where he handled the synchronization plan and implementation for synchronization of Microwave Network and Media Gateway, MSS, and Core Network. SSU Implementation Planning and Optimization with respect to IP RAN, Mobile Backhaul Solution- Optimization of Existing Microwave Network to Ethernet, Microwave Hybrid Solution, Convergence to all IP, SIU Implementation for conversion to IP of Existing BTS,GB over IP.His area of expertise includes Hadoop, Openstack, DevOps, Kubernetes, Dockers, Amazon web services, Apache Spark, Apache Storm, Apache Kafka, Hbase, Solr, Apache FlinkNutch, Mapreduce, Pig, Hive, Flume, Scoop, ElasticSearch, and programming expertise includes Python, Angular.js, and Node.js.

Sujets

• Informatique
• Artificial intelligence

Informations

• Publié par: BPB Publications
• Date de parution: 28 décembre 2019
• Nombre de lectures: 5
• EAN13: 9789389328691
• Langue: English
• Poids de l'ouvrage: 1 Mo

Extrait

Artificial Intelligence and Deep Learning for Decision Makers

A Growth Hacker’s Guide to Cutting Edge Technologies

by
Dr. Jagreet Kaur
Navdeep Singh Gill
FIRST EDITION 2020
Copyright © BPB Publications, India
ISBN: 978-93-89328-684
All Rights Reserved. No part of this publication may be reproduced or distributed 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.
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The information contained in this book is true to correct and the best of author’s & publisher’s knowledge. The author has made every effort to ensure the accuracy of these publications, but cannot be held responsible for any loss or damage arising from any information in this book.
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Dedicated to
Our Parents Late S. Ajmer Singh and Mrs. Sarbjeet Kaur S. Balwinder Singh and Mrs. Kulwinder Kaur
Our Children Dilnawaz Kaur and Haralam Singh and Professor Sakattar Singh Sidhu
About the Authors
Dr. Jagreet Kaur is an author and a data scientist. She has been working as a Chief Operating Officer in Xenonstack for the last 5 years. With that, she is also as Chief Data Scientist and Chief Operating Officer in Akira AI. She has more than 14 years’ experience in the field of education and research in different areas, such as Database Security, Data Warehousing, Data Science, and Artificial Intelligence. She has done her B.tech from Guru Nanak Dev Engineering College, Ludhiana, and M.tech from Punjab Engineering College, Chandigarh. She completed her Ph.D. with Research Topic “Artificial Intelligence Based Analytical Platform for Predictive Analysis in Health Care”.
She started her career as a lecturer in Khalsa College for Women. After that, she worked in different reputed institutes like Guru Nanak Dev Engineering College and Punjab University, Chandigarh, as a lecturer and assistant professor. She also worked as an assistant professor at the Chandigarh College of Engineering and Technology for 6 years.
With 10 years of experience in Artificial Intelligence, Data Science, Academics with Statistical analysis, Practical AI Applications and Decision Science Solutions, she is pursuing her career with Akira Analytics currently, where she is responsible for Planning and Architecting Decision Science and Data Products using Text analytics, NLP, Deep Learning, Machine Learning, and Computer Vision. She is known for understanding, at a deep level, what customers need and want; driving information and analytics strategy; serving a business purpose; and for providing out-of-the-box, legitimate, and robust solutions for problems related to Artificial Intelligence, Data Science, Decision Science, Text analytics, NLP, Deep Learning, Machine Learning, and Computer Vision.
She also possesses an interest in research papers, and she has published 15 research papers, out of which 10 are international and 5 are national. She is also a member of the Reviewer Community in Springer Publisher. In her leisure time, she likes to attend workshops and conferences and wants to do programming to create different applications.
Navdeep Singh Gill is working as a Chief Executive Officer in Xenonstack and Product Architect in Akira.AI. From the past 8 years, he has been working on Automation, Analytics, and AI for Building AI-first Organizations and Defining Enterprise Data Strategy.
He has more than 15 years’ experience in the IT and Telecom industry. During these years, he worked with some of the well-known companies, like Ericsson, Reliance Communications Ltd., and HFCL Infotel.
With over 15 years’ experience in Network Transformation, Cloud Infrastructure Solutions, Big Data Solution, Machine Learning, IoT, AI, Digital Transformation, Real-Time Analytics Solutions, IoT Platform, and Analytics and Cloud-Native applications, he is leading the technical and cross-functional teams as well as carrying out deep, hands-on experience through all phases of an engagement, including strategy, conceptual design, proof of concept, and detailed architectural design.
Under his guidance, Xenonstack is building a strong team for Cloud-Native transformation, Enterprise Devops, DevSecOps, Data Engineering, DataOps and MLOPs, and AI Global Managed Services under the umbrella of NexaOps.
He also helps companies to transform to AI-First Organization and Cloud-Native through the strategic application of Data Science and Artificial Intelligence, Platform Strategy and Enterprise Data, and AI Strategy.
About the Reviewer
Dr. Sarbjeet Singh is a Professor in Computer Science and Engineering at the University Institute of Engineering and Technology, Panjab University, Chandigarh. He holds Ph.D. and M.E degrees from Thapar Institute of Engineering and Technology, Patiala, Punjab. He has over more than 15 years of teaching and research experience. He has, to his credit, more than 100 publications in international journals and conferences of repute. His research interests include machine learning, cloud computing, social network analysis, IoT, telecommunication and smart systems. He has successfully completed a research project under the RPS scheme, funded by AICTE, New Delhi in 2012 and currently working on a MeitY, New Delhi sponsored research project dealing with UAV based intelligent monitoring and surveillance systems. He has guided 3 Ph.D. and more than 20 master students for research in different areas of computer science and engineering. Besides this, he has delivered several expert talks in different colleges and universities and is on the panel of BOS of many institutions and universities. Dr. Singh is a Life Member of the Computer Society of India and the Indian Society for Technical Education.
Acknowledgements
First and foremost, we would like to thank God for giving us the courage to write this book. We would also like to thank everyone at BPB Publications for giving us this opportunity to publish our books.
We would like to acknowledge the people who meant a lot to us—our parents, Late S. Ajmer Singh & Mrs. Sarbjeet Kaur, and S. Balwinder Singh & Mrs. Kulwinder Kaur for showing trust in us and giving us the freedom to choose what we desired. We salute you for the selfless love, care, and sacrifice you gave to shape our life. We appreciate our kids—our daughter, Dilnawaz Kaur, and our son, Haralam Singh—for the patience they showed while we wrote our book. Words aren’t enough to say how thankful we are to the both of you. We consider ourselves the luckiest to have a lovely and caring family that stands by our side with their love and unlimited support.
We would also like to thank our teachers and our friends for their useful discussions and suggestions, right from deciding topics and writing the concepts to framing the questions.
Lastly, we would like to thank our critics –without their criticism, we would never be able to write this book.
— Dr. Jagreet Kaur — Navdeep Singh
Preface
This book is targeted towards business and organization leaders, technology enthusiasts, professionals, and managers who seek the knowledge of Artificial Intelligence and Deep Learning methods. Their aim is to understand what is Artificial Intelligence and what are the Deep Learning methods, which would lead to them understanding how to implement these methods in improving businesses and organizations. This book is organized in such a way that the fundamentals of Artificial Intelligence are firstly emphasized from the basics of human thinking capabilities towards the implementation of machine intelligence for decision-making processes. Then, the design of Deep Learning architecture, in which is a part of Machine Learning techniques, is highlighted within general applications in our current activities. Later in this book, the chapters are divided according to recent case studies, including healthcare, communications, transportation, social interactions, and financial management. Each chapter will feature an elementary explanation of the problems involved in the case study, followed by the design and applications of Artificial Intelligence solutions, analysis of current trends in solving the problems, and outlooks of potential improvements using new technologies. From this book, readers can expect to learn about the concept of Artificial Intelligence and Deep Learning methods and how to use them according to categorized case studies. The readers will be exposed to the applications of the methods, which can help them spark new ideas of solving problems, improve their businesses and organizations, as well as apply the knowledge of the methods in their own fields.
Chapter 1 : This chapter describes the introduction of Artificial Intelligence and Deep Learning methods. At first, the concept of the human thinking process, starting from the biochemical responses within the structure of neurons to the problem-solving steps through computational thinking skills, is covered. Then, the thinking concept is adapted to computer architecture, emphasizing the thinking process performed by the computer. This is expanded to a higher level of thinking, namely, intelligence and reasoning capabi