Neural Approaches to Conversational AI: Question Answering, Task-Oriented Dialogues and Social Chatbots

Neural Approaches to Conversational AI: Question Answering, Task-Oriented Dialogues and Social Chatbots

Author: Jianfeng Gao

Publisher: Foundations and Trends(r) in I

Published: 2019-02-21

Total Pages: 184

ISBN-13: 9781680835526

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This monograph is the first survey of neural approaches to conversational AI that targets Natural Language Processing and Information Retrieval audiences. It provides a comprehensive survey of the neural approaches to conversational AI that have been developed in the last few years, covering QA, task-oriented and social bots with a unified view of optimal decision making.The authors draw connections between modern neural approaches and traditional approaches, allowing readers to better understand why and how the research has evolved and to shed light on how they can move forward. They also present state-of-the-art approaches to training dialogue agents using both supervised and reinforcement learning. Finally, the authors sketch out the landscape of conversational systems developed in the research community and released in industry, demonstrating via case studies the progress that has been made and the challenges that are still being faced.Neural Approaches to Conversational AI is a valuable resource for students, researchers, and software developers. It provides a unified view, as well as a detailed presentation of the important ideas and insights needed to understand and create modern dialogue agents that will be instrumental to making world knowledge and services accessible to millions of users in ways that seem natural and intuitive.


Book Synopsis Neural Approaches to Conversational AI: Question Answering, Task-Oriented Dialogues and Social Chatbots by : Jianfeng Gao

Download or read book Neural Approaches to Conversational AI: Question Answering, Task-Oriented Dialogues and Social Chatbots written by Jianfeng Gao and published by Foundations and Trends(r) in I. This book was released on 2019-02-21 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph is the first survey of neural approaches to conversational AI that targets Natural Language Processing and Information Retrieval audiences. It provides a comprehensive survey of the neural approaches to conversational AI that have been developed in the last few years, covering QA, task-oriented and social bots with a unified view of optimal decision making.The authors draw connections between modern neural approaches and traditional approaches, allowing readers to better understand why and how the research has evolved and to shed light on how they can move forward. They also present state-of-the-art approaches to training dialogue agents using both supervised and reinforcement learning. Finally, the authors sketch out the landscape of conversational systems developed in the research community and released in industry, demonstrating via case studies the progress that has been made and the challenges that are still being faced.Neural Approaches to Conversational AI is a valuable resource for students, researchers, and software developers. It provides a unified view, as well as a detailed presentation of the important ideas and insights needed to understand and create modern dialogue agents that will be instrumental to making world knowledge and services accessible to millions of users in ways that seem natural and intuitive.

Neural Approaches to Conversational Information Retrieval

Neural Approaches to Conversational Information Retrieval

Author: Jianfeng Gao

Publisher: Springer Nature

Published: 2023-03-16

Total Pages: 217

ISBN-13: 3031230809

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This book surveys recent advances in Conversational Information Retrieval (CIR), focusing on neural approaches that have been developed in the last few years. Progress in deep learning has brought tremendous improvements in natural language processing (NLP) and conversational AI, leading to a plethora of commercial conversational services that allow naturally spoken and typed interaction, increasing the need for more human-centric interactions in IR. The book contains nine chapters. Chapter 1 motivates the research of CIR by reviewing the studies on how people search and subsequently defines a CIR system and a reference architecture which is described in detail in the rest of the book. Chapter 2 provides a detailed discussion of techniques for evaluating a CIR system – a goal-oriented conversational AI system with a human in the loop. Then Chapters 3 to 7 describe the algorithms and methods for developing the main CIR modules (or sub-systems). In Chapter 3, conversational document search is discussed, which can be viewed as a sub-system of the CIR system. Chapter 4 is about algorithms and methods for query-focused multi-document summarization. Chapter 5 describes various neural models for conversational machine comprehension, which generate a direct answer to a user query based on retrieved query-relevant documents, while Chapter 6 details neural approaches to conversational question answering over knowledge bases, which is fundamental to the knowledge base search module of a CIR system. Chapter 7 elaborates various techniques and models that aim to equip a CIR system with the capability of proactively leading a human-machine conversation. Chapter 8 reviews a variety of commercial systems for CIR and related tasks. It first presents an overview of research platforms and toolkits which enable scientists and practitioners to build conversational experiences, and continues with historical highlights and recent trends in a range of application areas. Chapter 9 eventually concludes the book with a brief discussion of research trends and areas for future work. The primary target audience of the book are the IR and NLP research communities. However, audiences with another background, such as machine learning or human-computer interaction, will also find it an accessible introduction to CIR.


Book Synopsis Neural Approaches to Conversational Information Retrieval by : Jianfeng Gao

Download or read book Neural Approaches to Conversational Information Retrieval written by Jianfeng Gao and published by Springer Nature. This book was released on 2023-03-16 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book surveys recent advances in Conversational Information Retrieval (CIR), focusing on neural approaches that have been developed in the last few years. Progress in deep learning has brought tremendous improvements in natural language processing (NLP) and conversational AI, leading to a plethora of commercial conversational services that allow naturally spoken and typed interaction, increasing the need for more human-centric interactions in IR. The book contains nine chapters. Chapter 1 motivates the research of CIR by reviewing the studies on how people search and subsequently defines a CIR system and a reference architecture which is described in detail in the rest of the book. Chapter 2 provides a detailed discussion of techniques for evaluating a CIR system – a goal-oriented conversational AI system with a human in the loop. Then Chapters 3 to 7 describe the algorithms and methods for developing the main CIR modules (or sub-systems). In Chapter 3, conversational document search is discussed, which can be viewed as a sub-system of the CIR system. Chapter 4 is about algorithms and methods for query-focused multi-document summarization. Chapter 5 describes various neural models for conversational machine comprehension, which generate a direct answer to a user query based on retrieved query-relevant documents, while Chapter 6 details neural approaches to conversational question answering over knowledge bases, which is fundamental to the knowledge base search module of a CIR system. Chapter 7 elaborates various techniques and models that aim to equip a CIR system with the capability of proactively leading a human-machine conversation. Chapter 8 reviews a variety of commercial systems for CIR and related tasks. It first presents an overview of research platforms and toolkits which enable scientists and practitioners to build conversational experiences, and continues with historical highlights and recent trends in a range of application areas. Chapter 9 eventually concludes the book with a brief discussion of research trends and areas for future work. The primary target audience of the book are the IR and NLP research communities. However, audiences with another background, such as machine learning or human-computer interaction, will also find it an accessible introduction to CIR.

Conversational AI

Conversational AI

Author: Michael McTear

Publisher: Morgan & Claypool Publishers

Published: 2020-10-30

Total Pages: 253

ISBN-13: 1636390323

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This book provides a comprehensive introduction to Conversational AI. While the idea of interacting with a computer using voice or text goes back a long way, it is only in recent years that this idea has become a reality with the emergence of digital personal assistants, smart speakers, and chatbots. Advances in AI, particularly in deep learning, along with the availability of massive computing power and vast amounts of data, have led to a new generation of dialogue systems and conversational interfaces. Current research in Conversational AI focuses mainly on the application of machine learning and statistical data-driven approaches to the development of dialogue systems. However, it is important to be aware of previous achievements in dialogue technology and to consider to what extent they might be relevant to current research and development. Three main approaches to the development of dialogue systems are reviewed: rule-based systems that are handcrafted using best practice guidelines; statistical data-driven systems based on machine learning; and neural dialogue systems based on end-to-end learning. Evaluating the performance and usability of dialogue systems has become an important topic in its own right, and a variety of evaluation metrics and frameworks are described. Finally, a number of challenges for future research are considered, including: multimodality in dialogue systems, visual dialogue; data efficient dialogue model learning; using knowledge graphs; discourse and dialogue phenomena; hybrid approaches to dialogue systems development; dialogue with social robots and in the Internet of Things; and social and ethical issues.


Book Synopsis Conversational AI by : Michael McTear

Download or read book Conversational AI written by Michael McTear and published by Morgan & Claypool Publishers. This book was released on 2020-10-30 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive introduction to Conversational AI. While the idea of interacting with a computer using voice or text goes back a long way, it is only in recent years that this idea has become a reality with the emergence of digital personal assistants, smart speakers, and chatbots. Advances in AI, particularly in deep learning, along with the availability of massive computing power and vast amounts of data, have led to a new generation of dialogue systems and conversational interfaces. Current research in Conversational AI focuses mainly on the application of machine learning and statistical data-driven approaches to the development of dialogue systems. However, it is important to be aware of previous achievements in dialogue technology and to consider to what extent they might be relevant to current research and development. Three main approaches to the development of dialogue systems are reviewed: rule-based systems that are handcrafted using best practice guidelines; statistical data-driven systems based on machine learning; and neural dialogue systems based on end-to-end learning. Evaluating the performance and usability of dialogue systems has become an important topic in its own right, and a variety of evaluation metrics and frameworks are described. Finally, a number of challenges for future research are considered, including: multimodality in dialogue systems, visual dialogue; data efficient dialogue model learning; using knowledge graphs; discourse and dialogue phenomena; hybrid approaches to dialogue systems development; dialogue with social robots and in the Internet of Things; and social and ethical issues.

Neural Approaches to Dynamics of Signal Exchanges

Neural Approaches to Dynamics of Signal Exchanges

Author: Anna Esposito

Publisher: Springer Nature

Published: 2019-09-18

Total Pages: 525

ISBN-13: 9811389500

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The book presents research that contributes to the development of intelligent dialog systems to simplify diverse aspects of everyday life, such as medical diagnosis and entertainment. Covering major thematic areas: machine learning and artificial neural networks; algorithms and models; and social and biometric data for applications in human–computer interfaces, it discusses processing of audio-visual signals for the detection of user-perceived states, the latest scientific discoveries in processing verbal (lexicon, syntax, and pragmatics), auditory (voice, intonation, vocal expressions) and visual signals (gestures, body language, facial expressions), as well as algorithms for detecting communication disorders, remote health-status monitoring, sentiment and affect analysis, social behaviors and engagement. Further, it examines neural and machine learning algorithms for the implementation of advanced telecommunication systems, communication with people with special needs, emotion modulation by computer contents, advanced sensors for tracking changes in real-life and automatic systems, as well as the development of advanced human–computer interfaces. The book does not focus on solving a particular problem, but instead describes the results of research that has positive effects in different fields and applications.


Book Synopsis Neural Approaches to Dynamics of Signal Exchanges by : Anna Esposito

Download or read book Neural Approaches to Dynamics of Signal Exchanges written by Anna Esposito and published by Springer Nature. This book was released on 2019-09-18 with total page 525 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents research that contributes to the development of intelligent dialog systems to simplify diverse aspects of everyday life, such as medical diagnosis and entertainment. Covering major thematic areas: machine learning and artificial neural networks; algorithms and models; and social and biometric data for applications in human–computer interfaces, it discusses processing of audio-visual signals for the detection of user-perceived states, the latest scientific discoveries in processing verbal (lexicon, syntax, and pragmatics), auditory (voice, intonation, vocal expressions) and visual signals (gestures, body language, facial expressions), as well as algorithms for detecting communication disorders, remote health-status monitoring, sentiment and affect analysis, social behaviors and engagement. Further, it examines neural and machine learning algorithms for the implementation of advanced telecommunication systems, communication with people with special needs, emotion modulation by computer contents, advanced sensors for tracking changes in real-life and automatic systems, as well as the development of advanced human–computer interfaces. The book does not focus on solving a particular problem, but instead describes the results of research that has positive effects in different fields and applications.

Conversational AI

Conversational AI

Author: Michael McTear

Publisher: Springer Nature

Published: 2022-05-31

Total Pages: 234

ISBN-13: 3031021762

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This book provides a comprehensive introduction to Conversational AI. While the idea of interacting with a computer using voice or text goes back a long way, it is only in recent years that this idea has become a reality with the emergence of digital personal assistants, smart speakers, and chatbots. Advances in AI, particularly in deep learning, along with the availability of massive computing power and vast amounts of data, have led to a new generation of dialogue systems and conversational interfaces. Current research in Conversational AI focuses mainly on the application of machine learning and statistical data-driven approaches to the development of dialogue systems. However, it is important to be aware of previous achievements in dialogue technology and to consider to what extent they might be relevant to current research and development. Three main approaches to the development of dialogue systems are reviewed: rule-based systems that are handcrafted using best practice guidelines; statistical data-driven systems based on machine learning; and neural dialogue systems based on end-to-end learning. Evaluating the performance and usability of dialogue systems has become an important topic in its own right, and a variety of evaluation metrics and frameworks are described. Finally, a number of challenges for future research are considered, including: multimodality in dialogue systems, visual dialogue; data efficient dialogue model learning; using knowledge graphs; discourse and dialogue phenomena; hybrid approaches to dialogue systems development; dialogue with social robots and in the Internet of Things; and social and ethical issues.


Book Synopsis Conversational AI by : Michael McTear

Download or read book Conversational AI written by Michael McTear and published by Springer Nature. This book was released on 2022-05-31 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive introduction to Conversational AI. While the idea of interacting with a computer using voice or text goes back a long way, it is only in recent years that this idea has become a reality with the emergence of digital personal assistants, smart speakers, and chatbots. Advances in AI, particularly in deep learning, along with the availability of massive computing power and vast amounts of data, have led to a new generation of dialogue systems and conversational interfaces. Current research in Conversational AI focuses mainly on the application of machine learning and statistical data-driven approaches to the development of dialogue systems. However, it is important to be aware of previous achievements in dialogue technology and to consider to what extent they might be relevant to current research and development. Three main approaches to the development of dialogue systems are reviewed: rule-based systems that are handcrafted using best practice guidelines; statistical data-driven systems based on machine learning; and neural dialogue systems based on end-to-end learning. Evaluating the performance and usability of dialogue systems has become an important topic in its own right, and a variety of evaluation metrics and frameworks are described. Finally, a number of challenges for future research are considered, including: multimodality in dialogue systems, visual dialogue; data efficient dialogue model learning; using knowledge graphs; discourse and dialogue phenomena; hybrid approaches to dialogue systems development; dialogue with social robots and in the Internet of Things; and social and ethical issues.

Conversational Artificial Intelligence

Conversational Artificial Intelligence

Author: Romil Rawat

Publisher: John Wiley & Sons

Published: 2024-03-06

Total Pages: 804

ISBN-13: 1394200560

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This book reviews present state-of-the-art research related to the security of cloud computing including developments in conversational AI applications. It is particularly suited for those that bridge the academic world and industry, allowing readers to understand the security concerns in advanced security solutions for conversational AI in the cloud platform domain by reviewing present and evolving security solutions, their limitations, and future research directions. Conversational AI combines natural language processing (NLP) with traditional software like chatbots, voice assistants, or an interactive voice recognition system to help customers through either a spoken or typed interface. Conversational chatbots that respond to questions promptly and accurately to help customers are a fascinating development since they make the customer service industry somewhat self-sufficient. A well-automated chatbot can decimate staffing needs, but creating one is a time-consuming process. Voice recognition technologies are becoming more critical as AI assistants like Alexa become more popular. Chatbots in the corporate world have advanced technical connections with clients thanks to improvements in artificial intelligence. However, these chatbots’ increased access to sensitive information has raised serious security concerns. Threats are one-time events such as malware and DDOS (Distributed Denial of Service) assaults. Targeted strikes on companies are familiar and frequently lock workers out. User privacy violations are becoming more common, emphasizing the dangers of employing chatbots. Vulnerabilities are systemic problems that enable thieves to break in. Vulnerabilities allow threats to enter the system, hence they are inextricably linked. Malicious chatbots are widely used to spam and advertise in chat rooms by imitating human behavior and discussions, or to trick individuals into disclosing personal information like bank account details.


Book Synopsis Conversational Artificial Intelligence by : Romil Rawat

Download or read book Conversational Artificial Intelligence written by Romil Rawat and published by John Wiley & Sons. This book was released on 2024-03-06 with total page 804 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews present state-of-the-art research related to the security of cloud computing including developments in conversational AI applications. It is particularly suited for those that bridge the academic world and industry, allowing readers to understand the security concerns in advanced security solutions for conversational AI in the cloud platform domain by reviewing present and evolving security solutions, their limitations, and future research directions. Conversational AI combines natural language processing (NLP) with traditional software like chatbots, voice assistants, or an interactive voice recognition system to help customers through either a spoken or typed interface. Conversational chatbots that respond to questions promptly and accurately to help customers are a fascinating development since they make the customer service industry somewhat self-sufficient. A well-automated chatbot can decimate staffing needs, but creating one is a time-consuming process. Voice recognition technologies are becoming more critical as AI assistants like Alexa become more popular. Chatbots in the corporate world have advanced technical connections with clients thanks to improvements in artificial intelligence. However, these chatbots’ increased access to sensitive information has raised serious security concerns. Threats are one-time events such as malware and DDOS (Distributed Denial of Service) assaults. Targeted strikes on companies are familiar and frequently lock workers out. User privacy violations are becoming more common, emphasizing the dangers of employing chatbots. Vulnerabilities are systemic problems that enable thieves to break in. Vulnerabilities allow threats to enter the system, hence they are inextricably linked. Malicious chatbots are widely used to spam and advertise in chat rooms by imitating human behavior and discussions, or to trick individuals into disclosing personal information like bank account details.

ChatGPT 101

ChatGPT 101

Author: Franco L. Meyer

Publisher: epubli

Published: 2023-06-29

Total Pages: 62

ISBN-13: 3757562518

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In diesem einzigartigen Buch erfahren Sie, wie Sie ChatGPT und gezielte Fragen zu Ihrem Vorteil nutzen. Entdecken Sie die Macht, die richtigen Fragen zu stellen, und lernen Sie wie Sie ChatGPT optimal nutzen können. Tauchen Sie ein in die faszinierende Welt der künstlichen Intelligenz und sehen Sie, wie präzise und gut formulierte Abfragen Ihnen die Antworten liefern können, die Sie brauchen. Ob Sie ChatGPT im Kundenservice, in der Recherche oder bei der persönlichen Unterstützung nutzen – Mit den richtigen Fragen können Sie Ergebnisse auf die nächste Ebene bringen. Tauchen Sie ein in die Kunst des Abfragens und werden Sie ChatGPT - Meister!


Book Synopsis ChatGPT 101 by : Franco L. Meyer

Download or read book ChatGPT 101 written by Franco L. Meyer and published by epubli. This book was released on 2023-06-29 with total page 62 pages. Available in PDF, EPUB and Kindle. Book excerpt: In diesem einzigartigen Buch erfahren Sie, wie Sie ChatGPT und gezielte Fragen zu Ihrem Vorteil nutzen. Entdecken Sie die Macht, die richtigen Fragen zu stellen, und lernen Sie wie Sie ChatGPT optimal nutzen können. Tauchen Sie ein in die faszinierende Welt der künstlichen Intelligenz und sehen Sie, wie präzise und gut formulierte Abfragen Ihnen die Antworten liefern können, die Sie brauchen. Ob Sie ChatGPT im Kundenservice, in der Recherche oder bei der persönlichen Unterstützung nutzen – Mit den richtigen Fragen können Sie Ergebnisse auf die nächste Ebene bringen. Tauchen Sie ein in die Kunst des Abfragens und werden Sie ChatGPT - Meister!

Diabetes Digital Health, Telehealth, and Artificial Intelligence

Diabetes Digital Health, Telehealth, and Artificial Intelligence

Author: David C. Klonoff

Publisher: Elsevier

Published: 2024-06-21

Total Pages: 406

ISBN-13: 0443132437

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Diabetes Digital Health, Telehealth, and Artificial Intelligence explains how to develop and use the emerging technologies of digital health, telehealth, and artificial intelligence to address this important public health problem to deliver new hardware, software, and processes. The book explores trends in developing and deploying the three most important emerging technologies for diabetes: digital health, telehealth, and artificial intelligence. This book is essential to clinicians, scientists, engineers, industry professionals, regulators, and investors, offering the tools that will be used to create the next generation products to support a precision medicine approach to manage diabetes. According to the CDC, in the US there are 37 million people with diabetes and 96 million people with prediabetes. Diabetes triples the risk of myocardial infarction and stroke and is the leading cause of blindness, end stage renal failure, and amputations. The management of diabetes is becoming increasingly dominated by digital health tools consisting of wearable sensors, mobile applications providing decision support software, and wireless communication tools. Digital health provides new data streams that can be combined to create unique approaches for diabetes based on a precision medicine paradigm. Includes Artificial intelligence (AI) data for the prediction, diagnosis, treatment, and prognostication for diabetes as a model disease Describes the most important issues of our time that comprise the most important technologies currently being applied to diabetes Presented in a consistent easy to help those new to the field understand and compare/contrast various elements of digital health, telehealth, and artificial intelligence for diabetes


Book Synopsis Diabetes Digital Health, Telehealth, and Artificial Intelligence by : David C. Klonoff

Download or read book Diabetes Digital Health, Telehealth, and Artificial Intelligence written by David C. Klonoff and published by Elsevier. This book was released on 2024-06-21 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt: Diabetes Digital Health, Telehealth, and Artificial Intelligence explains how to develop and use the emerging technologies of digital health, telehealth, and artificial intelligence to address this important public health problem to deliver new hardware, software, and processes. The book explores trends in developing and deploying the three most important emerging technologies for diabetes: digital health, telehealth, and artificial intelligence. This book is essential to clinicians, scientists, engineers, industry professionals, regulators, and investors, offering the tools that will be used to create the next generation products to support a precision medicine approach to manage diabetes. According to the CDC, in the US there are 37 million people with diabetes and 96 million people with prediabetes. Diabetes triples the risk of myocardial infarction and stroke and is the leading cause of blindness, end stage renal failure, and amputations. The management of diabetes is becoming increasingly dominated by digital health tools consisting of wearable sensors, mobile applications providing decision support software, and wireless communication tools. Digital health provides new data streams that can be combined to create unique approaches for diabetes based on a precision medicine paradigm. Includes Artificial intelligence (AI) data for the prediction, diagnosis, treatment, and prognostication for diabetes as a model disease Describes the most important issues of our time that comprise the most important technologies currently being applied to diabetes Presented in a consistent easy to help those new to the field understand and compare/contrast various elements of digital health, telehealth, and artificial intelligence for diabetes

Artificial Intelligence in Insurance and Finance

Artificial Intelligence in Insurance and Finance

Author: Glenn Fung

Publisher: Frontiers Media SA

Published: 2022-01-04

Total Pages: 135

ISBN-13: 2889718115

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Luisa Fernanda Polania Cabrera is an Experienced Professional at Target Corporation (United States). Victor Wu is a Product Manager at GitLab Inc, San Francisco, United States. Sou-Cheng Choi is a Consulting Principle Data Scientist at Allstate Corporation. Lawrence Kwan Ho Ma is the Founder, Director and Chief Scientist of Valigo Limited and Founder, CEO and Chief Scientist of EMALI.IO Limited. Glenn M. Fung is the Chief Research Scientist at American Family Insurance.


Book Synopsis Artificial Intelligence in Insurance and Finance by : Glenn Fung

Download or read book Artificial Intelligence in Insurance and Finance written by Glenn Fung and published by Frontiers Media SA. This book was released on 2022-01-04 with total page 135 pages. Available in PDF, EPUB and Kindle. Book excerpt: Luisa Fernanda Polania Cabrera is an Experienced Professional at Target Corporation (United States). Victor Wu is a Product Manager at GitLab Inc, San Francisco, United States. Sou-Cheng Choi is a Consulting Principle Data Scientist at Allstate Corporation. Lawrence Kwan Ho Ma is the Founder, Director and Chief Scientist of Valigo Limited and Founder, CEO and Chief Scientist of EMALI.IO Limited. Glenn M. Fung is the Chief Research Scientist at American Family Insurance.

Machine Learning and Artificial Intelligence in Marketing and Sales

Machine Learning and Artificial Intelligence in Marketing and Sales

Author: Niladri Syam

Publisher: Emerald Group Publishing

Published: 2021-03-10

Total Pages: 177

ISBN-13: 1800438826

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Machine Learning and Artificial Intelligence in Marketing and Sales explores the ideas, and the statistical and mathematical concepts, behind Artificial Intelligence (AI) and machine learning models, as applied to marketing and sales, without getting lost in the details of mathematical derivations and computer programming.


Book Synopsis Machine Learning and Artificial Intelligence in Marketing and Sales by : Niladri Syam

Download or read book Machine Learning and Artificial Intelligence in Marketing and Sales written by Niladri Syam and published by Emerald Group Publishing. This book was released on 2021-03-10 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning and Artificial Intelligence in Marketing and Sales explores the ideas, and the statistical and mathematical concepts, behind Artificial Intelligence (AI) and machine learning models, as applied to marketing and sales, without getting lost in the details of mathematical derivations and computer programming.