Advanced Analytics And Deep Learning Models

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Advanced Analytics and Deep Learning Models

Archana Mire,Shaveta Malik,Amit Kumar Tyagi
Advanced Analytics and Deep Learning Models Book PDF

Author : Archana Mire,Shaveta Malik,Amit Kumar Tyagi
Publisher : John Wiley & Sons
Page : 436 pages
File Size : 55,7 Mb
Release : 2022-06-01
Category : Computers
ISBN : 9781119791751

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Advanced Analytics and Deep Learning Models by Archana Mire,Shaveta Malik,Amit Kumar Tyagi Pdf

Advanced Analytics and Deep Learning Models The book provides readers with an in-depth understanding of concepts and technologies related to the importance of analytics and deep learning in many useful real-world applications such as e-healthcare, transportation, agriculture, stock market, etc. Advanced analytics is a mixture of machine learning, artificial intelligence, graphs, text mining, data mining, semantic analysis. It is an approach to data analysis. Beyond the traditional business intelligence, it is a semi and autonomous analysis of data by using different techniques and tools. However, deep learning and data analysis both are high centers of data science. Almost all the private and public organizations collect heavy amounts of data, i.e., domain-specific data. Many small/large companies are exploring large amounts of data for existing and future technology. Deep learning is also exploring large amounts of unsupervised data making it beneficial and effective for big data. Deep learning can be used to deal with all kinds of problems and challenges that include collecting unlabeled and uncategorized raw data, extracting complex patterns from a large amount of data, retrieving fast information, tagging data, etc. This book contains 16 chapters on artificial intelligence, machine learning, deep learning, and their uses in many useful sectors like stock market prediction, a recommendation system for better service selection, e-healthcare, telemedicine, transportation. There are also chapters on innovations and future opportunities with fog computing/cloud computing and artificial intelligence. Audience Researchers in artificial intelligence, big data, computer science, and electronic engineering, as well as industry engineers in healthcare, telemedicine, transportation, and the financial sector. The book will also be a great source for software engineers and advanced students who are beginners in the field of advanced analytics in deep learning.

Advanced Deep Learning Applications in Big Data Analytics

Bouarara, Hadj Ahmed
Advanced Deep Learning Applications in Big Data Analytics Book PDF

Author : Bouarara, Hadj Ahmed
Publisher : IGI Global
Page : 351 pages
File Size : 55,9 Mb
Release : 2020-10-16
Category : Computers
ISBN : 9781799827931

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Advanced Deep Learning Applications in Big Data Analytics by Bouarara, Hadj Ahmed Pdf

Interest in big data has swelled within the scholarly community as has increased attention to the internet of things (IoT). Algorithms are constructed in order to parse and analyze all this data to facilitate the exchange of information. However, big data has suffered from problems in connectivity, scalability, and privacy since its birth. The application of deep learning algorithms has helped process those challenges and remains a major issue in today’s digital world. Advanced Deep Learning Applications in Big Data Analytics is a pivotal reference source that aims to develop new architecture and applications of deep learning algorithms in big data and the IoT. Highlighting a wide range of topics such as artificial intelligence, cloud computing, and neural networks, this book is ideally designed for engineers, data analysts, data scientists, IT specialists, programmers, marketers, entrepreneurs, researchers, academicians, and students.

Fundamentals of Machine Learning for Predictive Data Analytics, second edition

John D. Kelleher,Brian Mac Namee,Aoife D'Arcy
Fundamentals of Machine Learning for Predictive Data Analytics second edition Book PDF

Author : John D. Kelleher,Brian Mac Namee,Aoife D'Arcy
Publisher : MIT Press
Page : 853 pages
File Size : 42,8 Mb
Release : 2020-10-20
Category : Computers
ISBN : 9780262361101

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Fundamentals of Machine Learning for Predictive Data Analytics, second edition by John D. Kelleher,Brian Mac Namee,Aoife D'Arcy Pdf

The second edition of a comprehensive introduction to machine learning approaches used in predictive data analytics, covering both theory and practice. Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context. This second edition covers recent developments in machine learning, especially in a new chapter on deep learning, and two new chapters that go beyond predictive analytics to cover unsupervised learning and reinforcement learning.

Big Data Analytics Methods

Peter Ghavami
Big Data Analytics Methods Book PDF

Author : Peter Ghavami
Publisher : Walter de Gruyter GmbH & Co KG
Page : 282 pages
File Size : 44,5 Mb
Release : 2019-12-16
Category : Business & Economics
ISBN : 9781547401581

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Big Data Analytics Methods by Peter Ghavami Pdf

Big Data Analytics Methods unveils secrets to advanced analytics techniques ranging from machine learning, random forest classifiers, predictive modeling, cluster analysis, natural language processing (NLP), Kalman filtering and ensembles of models for optimal accuracy of analysis and prediction. More than 100 analytics techniques and methods provide big data professionals, business intelligence professionals and citizen data scientists insight on how to overcome challenges and avoid common pitfalls and traps in data analytics. The book offers solutions and tips on handling missing data, noisy and dirty data, error reduction and boosting signal to reduce noise. It discusses data visualization, prediction, optimization, artificial intelligence, regression analysis, the Cox hazard model and many analytics using case examples with applications in the healthcare, transportation, retail, telecommunication, consulting, manufacturing, energy and financial services industries. This book's state of the art treatment of advanced data analytics methods and important best practices will help readers succeed in data analytics.

Big Data Analytics Methods

Peter Ghavami
Big Data Analytics Methods Book PDF

Author : Peter Ghavami
Publisher : Createspace Independent Publishing Platform
Page : 304 pages
File Size : 48,9 Mb
Release : 2016-03-06
Category : Electronic
ISBN : 1530414830

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Big Data Analytics Methods by Peter Ghavami Pdf

Big Data Analytics Methods unveils secrets to advanced analytics techniques ranging from machine learning, random forest classifiers, predictive modeling, cluster analysis, natural language processing (NLP), Kalman filtering and ensemble of models for optimal accuracy of analysis and prediction. More than 100 analytics techniques and methods are covered. The book offers solutions and tips on handling missing data, noisy and dirty data, error reduction and boosting signal to reduce noise. This book is ideal as a text book for a course or as a reference for data scientists, data engineers, data analysts, Business intelligence practitioners, and business managers. It covers 10 chapters that discuss natural language processing (NLP), data visualization, prediction, optimization, artificial intelligence, regression analysis, cox hazard model and many analytics use case examples with applications in healthcare, transportation, retail, telecommunication, consulting, manufacturing, energy and financial services. Big Data Analytics Methods Is a must read for those who wish to gain confidence and knowledge about big data and advanced analytics techniques. Read this book and confidently speak, lead and guide others about machine learning, neural networks, NLP, deep learning, and over 100 other analytics techniques. This book is fun and easy to read. It starts with simple and broad explanation of methods and gradually introduces more technical terms and techniques layer by layer. It finally introduces the underlying mathematical terms for those who want a mathematical foundation of the analytics methods. This book is one of a kind as it provides state of the art in advanced data analytics methods with important best practices to ensure the reader's success in data analytics.

Integrating Deep Learning Algorithms to Overcome Challenges in Big Data Analytics

R. Sujatha,S. L. Aarthy,R. Vettriselvan
Integrating Deep Learning Algorithms to Overcome Challenges in Big Data Analytics Book PDF

Author : R. Sujatha,S. L. Aarthy,R. Vettriselvan
Publisher : CRC Press
Page : 216 pages
File Size : 50,6 Mb
Release : 2021-09-22
Category : Technology & Engineering
ISBN : 9781000454536

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Integrating Deep Learning Algorithms to Overcome Challenges in Big Data Analytics by R. Sujatha,S. L. Aarthy,R. Vettriselvan Pdf

Data science revolves around two giants: Big Data analytics and Deep Learning. It is becoming challenging to handle and retrieve useful information due to how fast data is expanding. This book presents the technologies and tools to simplify and streamline the formation of Big Data as well as Deep Learning systems. This book discusses how Big Data and Deep Learning hold the potential to significantly increase data understanding and decision-making. It also covers numerous applications in healthcare, education, communication, media, and entertainment. Integrating Deep Learning Algorithms to Overcome Challenges in Big Data Analytics offers innovative platforms for integrating Big Data and Deep Learning and presents issues related to adequate data storage, semantic indexing, data tagging, and fast information retrieval. FEATURES Provides insight into the skill set that leverages one’s strength to act as a good data analyst Discusses how Big Data and Deep Learning hold the potential to significantly increase data understanding and help in decision-making Covers numerous potential applications in healthcare, education, communication, media, and entertainment Offers innovative platforms for integrating Big Data and Deep Learning Presents issues related to adequate data storage, semantic indexing, data tagging, and fast information retrieval from Big Data This book is aimed at industry professionals, academics, research scholars, system modelers, and simulation experts.

Deep Learning for Data Analytics

Himansu Das,Chittaranjan Pradhan,Nilanjan Dey
Deep Learning for Data Analytics Book PDF

Author : Himansu Das,Chittaranjan Pradhan,Nilanjan Dey
Publisher : Academic Press
Page : 220 pages
File Size : 43,7 Mb
Release : 2020-05-29
Category : Science
ISBN : 9780128226087

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Deep Learning for Data Analytics by Himansu Das,Chittaranjan Pradhan,Nilanjan Dey Pdf

Deep learning, a branch of Artificial Intelligence and machine learning, has led to new approaches to solving problems in a variety of domains including data science, data analytics and biomedical engineering. Deep Learning for Data Analytics: Foundations, Biomedical Applications and Challenges provides readers with a focused approach for the design and implementation of deep learning concepts using data analytics techniques in large scale environments. Deep learning algorithms are based on artificial neural network models to cascade multiple layers of nonlinear processing, which aids in feature extraction and learning in supervised and unsupervised ways, including classification and pattern analysis. Deep learning transforms data through a cascade of layers, helping systems analyze and process complex data sets. Deep learning algorithms extract high level complex data and process these complex sets to relatively simpler ideas formulated in the preceding level of the hierarchy. The authors of this book focus on suitable data analytics methods to solve complex real world problems such as medical image recognition, biomedical engineering, and object tracking using deep learning methodologies. The book provides a pragmatic direction for researchers who wish to analyze large volumes of data for business, engineering, and biomedical applications. Deep learning architectures including deep neural networks, recurrent neural networks, and deep belief networks can be used to help resolve problems in applications such as natural language processing, speech recognition, computer vision, bioinoformatics, audio recognition, drug design, and medical image analysis. Presents the latest advances in Deep Learning for data analytics and biomedical engineering applications. Discusses Deep Learning techniques as they are being applied in the real world of biomedical engineering and data science, including Deep Learning networks, deep feature learning, deep learning toolboxes, performance evaluation, Deep Learning optimization, deep auto-encoders, and deep neural networks Provides readers with an introduction to Deep Learning, along with coverage of deep belief networks, convolutional neural networks, Restricted Boltzmann Machines, data analytics basics, enterprise data science, predictive analysis, optimization for Deep Learning, and feature selection using Deep Learning

Data Analytics

Anthony S. Williams
Data Analytics Book PDF

Author : Anthony S. Williams
Publisher : Anthony S. Williams
Page : 225 pages
File Size : 45,8 Mb
Release : 2024-06-26
Category : Computers
ISBN : 8210379456XXX

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Data Analytics by Anthony S. Williams Pdf

A Book Bundle of Data Analytics for Beginners AND Deep Learning with Keras Data Analytics for Beginners: Introduction to Data Analytics Knowing the data generated by your business every day is a key to success in the Data Analytic World that you are competing in. As there is so much data so, the organizations need to collect and store them. The data becomes valuable to businesses when it is analyzed. Prior to the recent rise in analytics, businesses and organizations did not have the capacity to analyze a great deal of data, so a relatively small amount was maintained. In today's data-driven world, anything and everything may have significance, so there has been an attempt to record and keep virtually any data that we have the capacity to collect; and we have a great deal of capacity. There is so much to learn in this bundle about data analytics and I do invite you to grab your copy today and get started! Deep Learning with Keras: Introduction to Deep Learning with Keras This book will introduce you to various deep learning models in Keras, and you will see how different neural networks can be used in real-world examples as well as in various scientific fields. You will explore various Keras algorithms like the simplest linear regression or more complex deep convolutional network. You will get to know what is the difference between supervised and unsupervised deep learning and you will be able to implement various algorithms in Keras by yourself as you follow step-by-step guide in this book. You will explore various applications of deep learning models such as speech recognition systems, natural language processing, and video game development. A whole new world will open in front of you since, by the time you reach the final page of this book, you will be a Keras expert and ready for your deep-learning projects. By downloading this BOOK BUNDLE you will discover... Data Analytics for Beginners: Putting Data Analytics to Work The Rise of Data Analytics Big Data Defined Cluster Analysis Applications of Cluster Analysis Commonly Graphed Information Data Visualization Four Important Features of Data Visualization Software Big Data Impact Envisaged by 2020 Pros and Cons of Big Data Analytics And of course much more! Deep Learning with Keras: Deep Neural Network Neural Network Elements Keras Models Sequential Model Functional API Model Keras Layers Core Keras Layers Convolutional Keras Layers Recurrent Keras Layers Deep Learning Algorithms Supervised Learning Algorithms Applications of Deep Learning Models Automatic Speech and Image Recognition Natural Language Processing Video Game Development Real World Applications And of course much more! Download this BOOK BUNDLE now and SAVE MONEY!!

Machine Learning and Big Data Analytics Paradigms: Analysis, Applications and Challenges

Aboul Ella Hassanien,Ashraf Darwish
Machine Learning and Big Data Analytics Paradigms Analysis Applications and Challenges Book PDF

Author : Aboul Ella Hassanien,Ashraf Darwish
Publisher : Springer Nature
Page : 648 pages
File Size : 55,9 Mb
Release : 2020-12-14
Category : Computers
ISBN : 9783030593384

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Machine Learning and Big Data Analytics Paradigms: Analysis, Applications and Challenges by Aboul Ella Hassanien,Ashraf Darwish Pdf

This book is intended to present the state of the art in research on machine learning and big data analytics. The accepted chapters covered many themes including artificial intelligence and data mining applications, machine learning and applications, deep learning technology for big data analytics, and modeling, simulation, and security with big data. It is a valuable resource for researchers in the area of big data analytics and its applications.

Deep Learning Techniques and Optimization Strategies in Big Data Analytics

Thomas, J. Joshua,Karagoz, Pinar,Ahamed, B. Bazeer,Vasant, Pandian
Deep Learning Techniques and Optimization Strategies in Big Data Analytics Book PDF

Author : Thomas, J. Joshua,Karagoz, Pinar,Ahamed, B. Bazeer,Vasant, Pandian
Publisher : IGI Global
Page : 355 pages
File Size : 40,5 Mb
Release : 2019-11-29
Category : Computers
ISBN : 9781799811947

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Deep Learning Techniques and Optimization Strategies in Big Data Analytics by Thomas, J. Joshua,Karagoz, Pinar,Ahamed, B. Bazeer,Vasant, Pandian Pdf

Many approaches have sprouted from artificial intelligence (AI) and produced major breakthroughs in the computer science and engineering industries. Deep learning is a method that is transforming the world of data and analytics. Optimization of this new approach is still unclear, however, and there’s a need for research on the various applications and techniques of deep learning in the field of computing. Deep Learning Techniques and Optimization Strategies in Big Data Analytics is a collection of innovative research on the methods and applications of deep learning strategies in the fields of computer science and information systems. While highlighting topics including data integration, computational modeling, and scheduling systems, this book is ideally designed for engineers, IT specialists, data analysts, data scientists, engineers, researchers, academicians, and students seeking current research on deep learning methods and its application in the digital industry.

Applied Advanced Analytics

Arnab Kumar Laha
Applied Advanced Analytics Book PDF

Author : Arnab Kumar Laha
Publisher : Springer Nature
Page : 236 pages
File Size : 45,7 Mb
Release : 2021-06-08
Category : Business & Economics
ISBN : 9789813366565

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Applied Advanced Analytics by Arnab Kumar Laha Pdf

This book covers several new areas in the growing field of analytics with some innovative applications in different business contexts, and consists of selected presentations at the 6th IIMA International Conference on Advanced Data Analysis, Business Analytics and Intelligence. The book is conceptually divided in seven parts. The first part gives expository briefs on some topics of current academic and practitioner interests, such as data streams, binary prediction and reliability shock models. In the second part, the contributions look at artificial intelligence applications with chapters related to explainable AI, personalized search and recommendation, and customer retention management. The third part deals with credit risk analytics, with chapters on optimization of credit limits and mitigation of agricultural lending risks. In its fourth part, the book explores analytics and data mining in the retail context. In the fifth part, the book presents some applications of analytics to operations management. This part has chapters related to improvement of furnace operations, forecasting food indices and analytics for improving student learning outcomes. The sixth part has contributions related to adaptive designs in clinical trials, stochastic comparisons of systems with heterogeneous components and stacking of models. The seventh and final part contains chapters related to finance and economics topics, such as role of infrastructure and taxation on economic growth of countries and connectedness of markets with heterogenous agents, The different themes ensure that the book would be of great value to practitioners, post-graduate students, research scholars and faculty teaching advanced business analytics courses.

Data Analytics

Anthony S. Williams
Data Analytics Book PDF

Author : Anthony S. Williams
Publisher : Anthony S. Williams
Page : 440 pages
File Size : 48,8 Mb
Release : 2024-06-26
Category : Computers
ISBN : 8210379456XXX

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Data Analytics by Anthony S. Williams Pdf

Data Analytics - 7 BOOK BUNDLE!! Book 1: Data Analytics For Beginners In this book you will learn: What is Data Analytics Types of Data Analytics Evolution of Data Analytics Big Data Defined Data Mining Data Visualization Cluster Analysis And of course much more! Book 2: Deep Learning With Keras In this book you will learn: Deep Neural Network Neural Network Elements Keras Models Sequential Model Functional API Model Keras Layers Core Keras Layers Convolutional Keras Layers Recurrent Keras Layers Deep Learning Algorithms Supervised Learning Algorithms Applications of Deep Learning Models Automatic Speech and Image Recognition Natural Language Processing And of course much more! Book 3: Analyzing Data With Power BI In this book you will learn: Basics of data analysis processes Fundamental data analysis algorithms Basic of data and text mining, data visualization, and business intelligence Techniques used for analysing quantitative data Basic data analysis tasks Conceptual, logical, and physical data models Power BI service and data modelling Creating reports and visualizations in Power BI And of course much more! Book 4: Reinforcement Learning With Python In this book you will learn: Types of fundamental machine learning algorithms in comparison to reinforcement learning Essentials of reinforcement learning process Marko decision processes and basic parameters How to integrate reinforcement learning algorithm using OpenAI Gym How to integrate Monte Carlo methods for prediction Monte Carlo tree search And much, much more... Book 5: Artificial Intelligence Python In this book you will learn: Different artificial intelligence approaches and goals How to define AI system Basic AI techniques Reinforcement learning And much, much more... Book 6: Text Analytics With Python In this book you will learn: Text analytics process How to build a corpus and analyze sentiment Named entity extraction with Groningen meaning bank corpus How to train your system Getting started with NLTK How to search syntax and tokenize sentences Automatic text summarization Stemming word and topic modeling with NLTK And much, much more... Book 7: Convolutional Neural Networks In Python In this book you will learn: Architecture of convolutional neural networks Solving computer vision tasks using convolutional neural networks Python and computer vision Automatic image and speech recognition Theano and TenroeFlow image recognition And of course much more! Download this book bundle NOW and SAVE money!!

Data Analytics and AI

Jay Liebowitz
Data Analytics and AI Book PDF

Author : Jay Liebowitz
Publisher : CRC Press
Page : 187 pages
File Size : 51,5 Mb
Release : 2020-08-06
Category : Computers
ISBN : 9781000094671

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Data Analytics and AI by Jay Liebowitz Pdf

Analytics and artificial intelligence (AI), what are they good for? The bandwagon keeps answering, absolutely everything! Analytics and artificial intelligence have captured the attention of everyone from top executives to the person in the street. While these disciplines have a relatively long history, within the last ten or so years they have exploded into corporate business and public consciousness. Organizations have rushed to embrace data-driven decision making. Companies everywhere are turning out products boasting that "artificial intelligence is included." We are indeed living in exciting times. The question we need to ask is, do we really know how to get business value from these exciting tools? Unfortunately, both the analytics and AI communities have not done a great job in collaborating and communicating with each other to build the necessary synergies. This book bridges the gap between these two critical fields. The book begins by explaining the commonalities and differences in the fields of data science, artificial intelligence, and autonomy by giving a historical perspective for each of these fields, followed by exploration of common technologies and current trends in each field. The book also readers introduces to applications of deep learning in industry with an overview of deep learning and its key architectures, as well as a survey and discussion of the main applications of deep learning. The book also presents case studies to illustrate applications of AI and analytics. These include a case study from the healthcare industry and an investigation of a digital transformation enabled by AI and analytics transforming a product-oriented company into one delivering solutions and services. The book concludes with a proposed AI-informed data analytics life cycle to be applied to unstructured data.

Machine Learning and Data Analytics for Predicting, Managing, and Monitoring Disease

Roy, Manikant,Gupta, Lovi Raj
Machine Learning and Data Analytics for Predicting Managing and Monitoring Disease Book PDF

Author : Roy, Manikant,Gupta, Lovi Raj
Publisher : IGI Global
Page : 241 pages
File Size : 42,9 Mb
Release : 2021-06-25
Category : Computers
ISBN : 9781799871903

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Machine Learning and Data Analytics for Predicting, Managing, and Monitoring Disease by Roy, Manikant,Gupta, Lovi Raj Pdf

Data analytics is proving to be an ally for epidemiologists as they join forces with data scientists to address the scale of crises. Analytics examined from many sources can derive insights and be used to study and fight global outbreaks. Pandemic analytics is a modern way to combat a problem as old as humanity itself: the proliferation of disease. Machine Learning and Data Analytics for Predicting, Managing, and Monitoring Disease explores different types of data and discusses how to prepare data for analysis, perform simple statistical analyses, create meaningful data visualizations, predict future trends from data, and more by applying cutting edge technology such as machine learning and data analytics in the wake of the COVID-19 pandemic. Covering a range of topics such as mental health analytics during COVID-19, data analysis and machine learning using Python, and statistical model development and deployment, it is ideal for researchers, academicians, data scientists, technologists, data analysts, diagnosticians, healthcare professionals, computer scientists, and students.

Advanced Analytics for Business

Mark Ryan,Luca Massaron
Advanced Analytics for Business Book PDF

Author : Mark Ryan,Luca Massaron
Publisher : Manning
Page : 0 pages
File Size : 41,9 Mb
Release : 2024-09-24
Category : Computers
ISBN : 1633438546

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Advanced Analytics for Business by Mark Ryan,Luca Massaron Pdf

Business runs on tabular data in databases, spreadsheets, and logs. Crunch that data using deep learning, gradient boosting, and other machine learning techniques. Every organization in the world stores data in tables. Advanced Analytics for Business reveals practical techniques for applying machine learning techniques like deep learning and gradient boosting to your company’s rows and columns. Inside Advanced Analytics for Business you’ll learn how to: Pick the right machine learning approach for your data Apply deep learning to tabular data Deploy tabular machine learning locally and in the cloud Pipelines to automatically train and maintain a model This book collects best practices, hard-won tips and tricks, and hands-on techniques for making sense of tabular data using advanced machine learning techniques. Inside, you’ll discover how to use XGBoost and LightGBM on tabular data, optimize deep learning libraries like TensorFlow and PyTorch for tabular data, and use cloud tools like Vertex AI to create an automated MLOps pipeline. Purchase of the print book includes a free eBook in PDF and ePub formats from Manning Publications. About the book Advanced Analytics for Business teaches you to train insightful machine learning models on common tabular data such as spreadsheets, databases, and logs. It covers classic machine learning techniques like gradient boosting and more contemporary deep learning approaches. You’ll find practical examples for every stage of the machine learning pipeline, such as using XGBoost and Keras to predict the prices of Airbnb listings in New York City and deploying a machine learning model on your local system with Flask. By the time you’re finished, you’ll be equipped with the skills to apply machine learning to the kinds of data you work with every day. About the reader For readers experienced with Python and the basics of machine learning. About the author Mark Ryan is a technical writing manager at Google. He studied computer science at the University of Waterloo and at the University of Toronto. In addition to a keen interest in deep learning with tabular data, Mark is interested in applications of large language models. Luca Massaron is a data scientist with more than a decade of experience in transforming data into smarter artifacts, solving real-world problems, and generating value for businesses and stakeholders. He is the author of bestselling books on AI, machine learning, and algorithms.