Author: Nicky Roberts
Publisher: My First A.I. Book
ISBN: 9781513654249
Category : Juvenile Fiction
Languages : en
Pages : 34
Book Description
Artificial Intelligence and Learning is a teaser in a series of books and pioneering book for kids on Artificial Intelligence (A.I.) which focuses on its chief concept: LEARNING. The My First A.I. Books Series introduces kids of all ages to the foundational concepts for Artificial Intelligence and the 4th Industrial/Human Revolution, AKA I4.0 or 4IR or IOT. Written by three global experts and active scientific researchers, Professors Fernando Buarque (Ph.D. in A.I. Imperial College London), Tshilidzi Marwala (Ph.D. in A.I. at University of Cambridge), and Nicky Roberts (Ph.D. in Mathematics Education at the University of Witwatersrand).This book and series are suitable for all kids starting their Artificial Intelligence journey. As a matter of fact, the future of humankind depends centrally on how A.I. will be produced and used. As such, little readers are encouraged to think and talk in an informed manner about A.I. topics. The story of this first book, sets the plot by delving into the evolution of human tools (up to the fourth human revolution), types of learning, the ingredients for adaptive computer programs (i.e. programs that are able to learn), and even provides a working definition of A.I. All the books of the series are packed with concepts and encourage inquiry. They aim to widen the kids' perspectives on, and also nurture their participation with, these new concepts and tools. All that in this amazing unfolding revolution - the Revolution of the Intelligence. The authors took care to include not only technical concepts, but humanistic and character-building values too. Thus, readers would acquire a good foundation for their future, which may even not be a technical one (but certainly will include A.I.). Ideally, this book should be read by the kids with an adult. It is handsomely complemented by five more books, which portrait five missions, detailing other chief functional A.I. concepts. In each mission the explorers are challenged to delve (and learn) five different ways of using A.I. on real-world problems. The other books in the My First A.I. Books Series are: -My First A.I. Book - Mission of Team-B is Searching -My First A.I. Book - Mission of Team-R is Predicting-My First A.I. Book - Mission of Team-I is Classifying-My First A.I. Book - Mission of Team-C is Optimizing-My First A.I. Book - Mission of Team-S is Interfacing
MY FIRST A.I. BOOK - Artificial Intelligence and Learning
Author: Nicky Roberts
Publisher: My First A.I. Book
ISBN: 9781513654249
Category : Juvenile Fiction
Languages : en
Pages : 34
Book Description
Artificial Intelligence and Learning is a teaser in a series of books and pioneering book for kids on Artificial Intelligence (A.I.) which focuses on its chief concept: LEARNING. The My First A.I. Books Series introduces kids of all ages to the foundational concepts for Artificial Intelligence and the 4th Industrial/Human Revolution, AKA I4.0 or 4IR or IOT. Written by three global experts and active scientific researchers, Professors Fernando Buarque (Ph.D. in A.I. Imperial College London), Tshilidzi Marwala (Ph.D. in A.I. at University of Cambridge), and Nicky Roberts (Ph.D. in Mathematics Education at the University of Witwatersrand).This book and series are suitable for all kids starting their Artificial Intelligence journey. As a matter of fact, the future of humankind depends centrally on how A.I. will be produced and used. As such, little readers are encouraged to think and talk in an informed manner about A.I. topics. The story of this first book, sets the plot by delving into the evolution of human tools (up to the fourth human revolution), types of learning, the ingredients for adaptive computer programs (i.e. programs that are able to learn), and even provides a working definition of A.I. All the books of the series are packed with concepts and encourage inquiry. They aim to widen the kids' perspectives on, and also nurture their participation with, these new concepts and tools. All that in this amazing unfolding revolution - the Revolution of the Intelligence. The authors took care to include not only technical concepts, but humanistic and character-building values too. Thus, readers would acquire a good foundation for their future, which may even not be a technical one (but certainly will include A.I.). Ideally, this book should be read by the kids with an adult. It is handsomely complemented by five more books, which portrait five missions, detailing other chief functional A.I. concepts. In each mission the explorers are challenged to delve (and learn) five different ways of using A.I. on real-world problems. The other books in the My First A.I. Books Series are: -My First A.I. Book - Mission of Team-B is Searching -My First A.I. Book - Mission of Team-R is Predicting-My First A.I. Book - Mission of Team-I is Classifying-My First A.I. Book - Mission of Team-C is Optimizing-My First A.I. Book - Mission of Team-S is Interfacing
Publisher: My First A.I. Book
ISBN: 9781513654249
Category : Juvenile Fiction
Languages : en
Pages : 34
Book Description
Artificial Intelligence and Learning is a teaser in a series of books and pioneering book for kids on Artificial Intelligence (A.I.) which focuses on its chief concept: LEARNING. The My First A.I. Books Series introduces kids of all ages to the foundational concepts for Artificial Intelligence and the 4th Industrial/Human Revolution, AKA I4.0 or 4IR or IOT. Written by three global experts and active scientific researchers, Professors Fernando Buarque (Ph.D. in A.I. Imperial College London), Tshilidzi Marwala (Ph.D. in A.I. at University of Cambridge), and Nicky Roberts (Ph.D. in Mathematics Education at the University of Witwatersrand).This book and series are suitable for all kids starting their Artificial Intelligence journey. As a matter of fact, the future of humankind depends centrally on how A.I. will be produced and used. As such, little readers are encouraged to think and talk in an informed manner about A.I. topics. The story of this first book, sets the plot by delving into the evolution of human tools (up to the fourth human revolution), types of learning, the ingredients for adaptive computer programs (i.e. programs that are able to learn), and even provides a working definition of A.I. All the books of the series are packed with concepts and encourage inquiry. They aim to widen the kids' perspectives on, and also nurture their participation with, these new concepts and tools. All that in this amazing unfolding revolution - the Revolution of the Intelligence. The authors took care to include not only technical concepts, but humanistic and character-building values too. Thus, readers would acquire a good foundation for their future, which may even not be a technical one (but certainly will include A.I.). Ideally, this book should be read by the kids with an adult. It is handsomely complemented by five more books, which portrait five missions, detailing other chief functional A.I. concepts. In each mission the explorers are challenged to delve (and learn) five different ways of using A.I. on real-world problems. The other books in the My First A.I. Books Series are: -My First A.I. Book - Mission of Team-B is Searching -My First A.I. Book - Mission of Team-R is Predicting-My First A.I. Book - Mission of Team-I is Classifying-My First A.I. Book - Mission of Team-C is Optimizing-My First A.I. Book - Mission of Team-S is Interfacing
The Essence of Artificial Intelligence
Author: Alison Cawsey
Publisher: Pearson
ISBN: 9780135717790
Category : Computers
Languages : en
Pages : 204
Book Description
A concise, practical introduction to artificial intelligence, this title starts with the fundamentals of knowledge representation, inference, expert systems, natural language processing, machine learning, neural networks, agents, robots, and much more. Examples and algorithms are presented throughout, and the book includes a complete glossary.
Publisher: Pearson
ISBN: 9780135717790
Category : Computers
Languages : en
Pages : 204
Book Description
A concise, practical introduction to artificial intelligence, this title starts with the fundamentals of knowledge representation, inference, expert systems, natural language processing, machine learning, neural networks, agents, robots, and much more. Examples and algorithms are presented throughout, and the book includes a complete glossary.
AI and Machine Learning for Coders
Author: Laurence Moroney
Publisher: O'Reilly Media
ISBN: 1492078166
Category : Computers
Languages : en
Pages : 393
Book Description
If you're looking to make a career move from programmer to AI specialist, this is the ideal place to start. Based on Laurence Moroney's extremely successful AI courses, this introductory book provides a hands-on, code-first approach to help you build confidence while you learn key topics. You'll understand how to implement the most common scenarios in machine learning, such as computer vision, natural language processing (NLP), and sequence modeling for web, mobile, cloud, and embedded runtimes. Most books on machine learning begin with a daunting amount of advanced math. This guide is built on practical lessons that let you work directly with the code. You'll learn: How to build models with TensorFlow using skills that employers desire The basics of machine learning by working with code samples How to implement computer vision, including feature detection in images How to use NLP to tokenize and sequence words and sentences Methods for embedding models in Android and iOS How to serve models over the web and in the cloud with TensorFlow Serving
Publisher: O'Reilly Media
ISBN: 1492078166
Category : Computers
Languages : en
Pages : 393
Book Description
If you're looking to make a career move from programmer to AI specialist, this is the ideal place to start. Based on Laurence Moroney's extremely successful AI courses, this introductory book provides a hands-on, code-first approach to help you build confidence while you learn key topics. You'll understand how to implement the most common scenarios in machine learning, such as computer vision, natural language processing (NLP), and sequence modeling for web, mobile, cloud, and embedded runtimes. Most books on machine learning begin with a daunting amount of advanced math. This guide is built on practical lessons that let you work directly with the code. You'll learn: How to build models with TensorFlow using skills that employers desire The basics of machine learning by working with code samples How to implement computer vision, including feature detection in images How to use NLP to tokenize and sequence words and sentences Methods for embedding models in Android and iOS How to serve models over the web and in the cloud with TensorFlow Serving
The Hundred-page Machine Learning Book
Author: Andriy Burkov
Publisher:
ISBN: 9781999579500
Category : Machine learning
Languages : en
Pages : 141
Book Description
Provides a practical guide to get started and execute on machine learning within a few days without necessarily knowing much about machine learning.The first five chapters are enough to get you started and the next few chapters provide you a good feel of more advanced topics to pursue.
Publisher:
ISBN: 9781999579500
Category : Machine learning
Languages : en
Pages : 141
Book Description
Provides a practical guide to get started and execute on machine learning within a few days without necessarily knowing much about machine learning.The first five chapters are enough to get you started and the next few chapters provide you a good feel of more advanced topics to pursue.
Pragmatic AI
Author: Noah Gift
Publisher: Addison-Wesley Professional
ISBN: 0134863917
Category : Computers
Languages : en
Pages : 720
Book Description
Master Powerful Off-the-Shelf Business Solutions for AI and Machine Learning Pragmatic AI will help you solve real-world problems with contemporary machine learning, artificial intelligence, and cloud computing tools. Noah Gift demystifies all the concepts and tools you need to get results—even if you don’t have a strong background in math or data science. Gift illuminates powerful off-the-shelf cloud offerings from Amazon, Google, and Microsoft, and demonstrates proven techniques using the Python data science ecosystem. His workflows and examples help you streamline and simplify every step, from deployment to production, and build exceptionally scalable solutions. As you learn how machine language (ML) solutions work, you’ll gain a more intuitive understanding of what you can achieve with them and how to maximize their value. Building on these fundamentals, you’ll walk step-by-step through building cloud-based AI/ML applications to address realistic issues in sports marketing, project management, product pricing, real estate, and beyond. Whether you’re a business professional, decision-maker, student, or programmer, Gift’s expert guidance and wide-ranging case studies will prepare you to solve data science problems in virtually any environment. Get and configure all the tools you’ll need Quickly review all the Python you need to start building machine learning applications Master the AI and ML toolchain and project lifecycle Work with Python data science tools such as IPython, Pandas, Numpy, Juypter Notebook, and Sklearn Incorporate a pragmatic feedback loop that continually improves the efficiency of your workflows and systems Develop cloud AI solutions with Google Cloud Platform, including TPU, Colaboratory, and Datalab services Define Amazon Web Services cloud AI workflows, including spot instances, code pipelines, boto, and more Work with Microsoft Azure AI APIs Walk through building six real-world AI applications, from start to finish Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.
Publisher: Addison-Wesley Professional
ISBN: 0134863917
Category : Computers
Languages : en
Pages : 720
Book Description
Master Powerful Off-the-Shelf Business Solutions for AI and Machine Learning Pragmatic AI will help you solve real-world problems with contemporary machine learning, artificial intelligence, and cloud computing tools. Noah Gift demystifies all the concepts and tools you need to get results—even if you don’t have a strong background in math or data science. Gift illuminates powerful off-the-shelf cloud offerings from Amazon, Google, and Microsoft, and demonstrates proven techniques using the Python data science ecosystem. His workflows and examples help you streamline and simplify every step, from deployment to production, and build exceptionally scalable solutions. As you learn how machine language (ML) solutions work, you’ll gain a more intuitive understanding of what you can achieve with them and how to maximize their value. Building on these fundamentals, you’ll walk step-by-step through building cloud-based AI/ML applications to address realistic issues in sports marketing, project management, product pricing, real estate, and beyond. Whether you’re a business professional, decision-maker, student, or programmer, Gift’s expert guidance and wide-ranging case studies will prepare you to solve data science problems in virtually any environment. Get and configure all the tools you’ll need Quickly review all the Python you need to start building machine learning applications Master the AI and ML toolchain and project lifecycle Work with Python data science tools such as IPython, Pandas, Numpy, Juypter Notebook, and Sklearn Incorporate a pragmatic feedback loop that continually improves the efficiency of your workflows and systems Develop cloud AI solutions with Google Cloud Platform, including TPU, Colaboratory, and Datalab services Define Amazon Web Services cloud AI workflows, including spot instances, code pipelines, boto, and more Work with Microsoft Azure AI APIs Walk through building six real-world AI applications, from start to finish Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.
The AI-First Company
Author: Ash Fontana
Publisher: Penguin
ISBN: 0593330315
Category : Business & Economics
Languages : en
Pages : 306
Book Description
Artificial Intelligence is transforming every industry, but if you want to win with AI, you have to put it first on your priority list. AI-First companies are the only trillion-dollar companies, and soon they will dominate even more industries, more definitively than ever before. These companies succeed by design--they collect valuable data from day one and use it to train predictive models that automate core functions. As a result, they learn faster and outpace the competition in the process. Thankfully, you don't need a Ph.D. to learn how to win with AI. In The AI-First Company, internationally-renowned startup investor Ash Fontana offers an executable guide for applying AI to business problems. It's a playbook made for real companies, with real budgets, that need strategies and tactics to effectively implement AI. Whether you're a new online retailer or a Fortune 500 company, Fontana will teach you how to: • Identify the most valuable data; • Build the teams that build AI; • Integrate AI with existing processes and keep it in check; • Measure and communicate its effectiveness; • Reinvest the profits from automation to compound competitive advantage. If the last fifty years were about getting AI to work in the lab, the next fifty years will be about getting AI to work for people, businesses, and society. It's not about building the right software -- it's about building the right AI. The AI-First Company is your guide to winning with artificial intelligence.
Publisher: Penguin
ISBN: 0593330315
Category : Business & Economics
Languages : en
Pages : 306
Book Description
Artificial Intelligence is transforming every industry, but if you want to win with AI, you have to put it first on your priority list. AI-First companies are the only trillion-dollar companies, and soon they will dominate even more industries, more definitively than ever before. These companies succeed by design--they collect valuable data from day one and use it to train predictive models that automate core functions. As a result, they learn faster and outpace the competition in the process. Thankfully, you don't need a Ph.D. to learn how to win with AI. In The AI-First Company, internationally-renowned startup investor Ash Fontana offers an executable guide for applying AI to business problems. It's a playbook made for real companies, with real budgets, that need strategies and tactics to effectively implement AI. Whether you're a new online retailer or a Fortune 500 company, Fontana will teach you how to: • Identify the most valuable data; • Build the teams that build AI; • Integrate AI with existing processes and keep it in check; • Measure and communicate its effectiveness; • Reinvest the profits from automation to compound competitive advantage. If the last fifty years were about getting AI to work in the lab, the next fifty years will be about getting AI to work for people, businesses, and society. It's not about building the right software -- it's about building the right AI. The AI-First Company is your guide to winning with artificial intelligence.
Artificial Intelligence
Author: David L. Poole
Publisher: Cambridge University Press
ISBN: 110719539X
Category : Computers
Languages : en
Pages : 821
Book Description
Artificial Intelligence presents a practical guide to AI, including agents, machine learning and problem-solving simple and complex domains.
Publisher: Cambridge University Press
ISBN: 110719539X
Category : Computers
Languages : en
Pages : 821
Book Description
Artificial Intelligence presents a practical guide to AI, including agents, machine learning and problem-solving simple and complex domains.
Hands-On Deep Learning Algorithms with Python
Author: Sudharsan Ravichandiran
Publisher: Packt Publishing Ltd
ISBN: 1789344514
Category : Computers
Languages : en
Pages : 498
Book Description
Understand basic to advanced deep learning algorithms, the mathematical principles behind them, and their practical applications. Key FeaturesGet up-to-speed with building your own neural networks from scratch Gain insights into the mathematical principles behind deep learning algorithmsImplement popular deep learning algorithms such as CNNs, RNNs, and more using TensorFlowBook Description Deep learning is one of the most popular domains in the AI space, allowing you to develop multi-layered models of varying complexities. This book introduces you to popular deep learning algorithms—from basic to advanced—and shows you how to implement them from scratch using TensorFlow. Throughout the book, you will gain insights into each algorithm, the mathematical principles behind it, and how to implement it in the best possible manner. The book starts by explaining how you can build your own neural networks, followed by introducing you to TensorFlow, the powerful Python-based library for machine learning and deep learning. Moving on, you will get up to speed with gradient descent variants, such as NAG, AMSGrad, AdaDelta, Adam, and Nadam. The book will then provide you with insights into RNNs and LSTM and how to generate song lyrics with RNN. Next, you will master the math for convolutional and capsule networks, widely used for image recognition tasks. Then you learn how machines understand the semantics of words and documents using CBOW, skip-gram, and PV-DM. Afterward, you will explore various GANs, including InfoGAN and LSGAN, and autoencoders, such as contractive autoencoders and VAE. By the end of this book, you will be equipped with all the skills you need to implement deep learning in your own projects. What you will learnImplement basic-to-advanced deep learning algorithmsMaster the mathematics behind deep learning algorithmsBecome familiar with gradient descent and its variants, such as AMSGrad, AdaDelta, Adam, and NadamImplement recurrent networks, such as RNN, LSTM, GRU, and seq2seq modelsUnderstand how machines interpret images using CNN and capsule networksImplement different types of generative adversarial network, such as CGAN, CycleGAN, and StackGANExplore various types of autoencoder, such as Sparse autoencoders, DAE, CAE, and VAEWho this book is for If you are a machine learning engineer, data scientist, AI developer, or simply want to focus on neural networks and deep learning, this book is for you. Those who are completely new to deep learning, but have some experience in machine learning and Python programming, will also find the book very helpful.
Publisher: Packt Publishing Ltd
ISBN: 1789344514
Category : Computers
Languages : en
Pages : 498
Book Description
Understand basic to advanced deep learning algorithms, the mathematical principles behind them, and their practical applications. Key FeaturesGet up-to-speed with building your own neural networks from scratch Gain insights into the mathematical principles behind deep learning algorithmsImplement popular deep learning algorithms such as CNNs, RNNs, and more using TensorFlowBook Description Deep learning is one of the most popular domains in the AI space, allowing you to develop multi-layered models of varying complexities. This book introduces you to popular deep learning algorithms—from basic to advanced—and shows you how to implement them from scratch using TensorFlow. Throughout the book, you will gain insights into each algorithm, the mathematical principles behind it, and how to implement it in the best possible manner. The book starts by explaining how you can build your own neural networks, followed by introducing you to TensorFlow, the powerful Python-based library for machine learning and deep learning. Moving on, you will get up to speed with gradient descent variants, such as NAG, AMSGrad, AdaDelta, Adam, and Nadam. The book will then provide you with insights into RNNs and LSTM and how to generate song lyrics with RNN. Next, you will master the math for convolutional and capsule networks, widely used for image recognition tasks. Then you learn how machines understand the semantics of words and documents using CBOW, skip-gram, and PV-DM. Afterward, you will explore various GANs, including InfoGAN and LSGAN, and autoencoders, such as contractive autoencoders and VAE. By the end of this book, you will be equipped with all the skills you need to implement deep learning in your own projects. What you will learnImplement basic-to-advanced deep learning algorithmsMaster the mathematics behind deep learning algorithmsBecome familiar with gradient descent and its variants, such as AMSGrad, AdaDelta, Adam, and NadamImplement recurrent networks, such as RNN, LSTM, GRU, and seq2seq modelsUnderstand how machines interpret images using CNN and capsule networksImplement different types of generative adversarial network, such as CGAN, CycleGAN, and StackGANExplore various types of autoencoder, such as Sparse autoencoders, DAE, CAE, and VAEWho this book is for If you are a machine learning engineer, data scientist, AI developer, or simply want to focus on neural networks and deep learning, this book is for you. Those who are completely new to deep learning, but have some experience in machine learning and Python programming, will also find the book very helpful.
Artificial Intelligence
Author: Melanie Mitchell
Publisher: Farrar, Straus and Giroux
ISBN: 0374715238
Category : Computers
Languages : en
Pages : 216
Book Description
“After reading Mitchell’s guide, you’ll know what you don’t know and what other people don’t know, even though they claim to know it. And that’s invaluable." –The New York Times A leading computer scientist brings human sense to the AI bubble No recent scientific enterprise has proved as alluring, terrifying, and filled with extravagant promise and frustrating setbacks as artificial intelligence. The award-winning author Melanie Mitchell, a leading computer scientist, now reveals AI’s turbulent history and the recent spate of apparent successes, grand hopes, and emerging fears surrounding it. In Artificial Intelligence, Mitchell turns to the most urgent questions concerning AI today: How intelligent—really—are the best AI programs? How do they work? What can they actually do, and when do they fail? How humanlike do we expect them to become, and how soon do we need to worry about them surpassing us? Along the way, she introduces the dominant models of modern AI and machine learning, describing cutting-edge AI programs, their human inventors, and the historical lines of thought underpinning recent achievements. She meets with fellow experts such as Douglas Hofstadter, the cognitive scientist and Pulitzer Prize–winning author of the modern classic Gödel, Escher, Bach, who explains why he is “terrified” about the future of AI. She explores the profound disconnect between the hype and the actual achievements in AI, providing a clear sense of what the field has accomplished and how much further it has to go. Interweaving stories about the science of AI and the people behind it, Artificial Intelligence brims with clear-sighted, captivating, and accessible accounts of the most interesting and provocative modern work in the field, flavored with Mitchell’s humor and personal observations. This frank, lively book is an indispensable guide to understanding today’s AI, its quest for “human-level” intelligence, and its impact on the future for us all.
Publisher: Farrar, Straus and Giroux
ISBN: 0374715238
Category : Computers
Languages : en
Pages : 216
Book Description
“After reading Mitchell’s guide, you’ll know what you don’t know and what other people don’t know, even though they claim to know it. And that’s invaluable." –The New York Times A leading computer scientist brings human sense to the AI bubble No recent scientific enterprise has proved as alluring, terrifying, and filled with extravagant promise and frustrating setbacks as artificial intelligence. The award-winning author Melanie Mitchell, a leading computer scientist, now reveals AI’s turbulent history and the recent spate of apparent successes, grand hopes, and emerging fears surrounding it. In Artificial Intelligence, Mitchell turns to the most urgent questions concerning AI today: How intelligent—really—are the best AI programs? How do they work? What can they actually do, and when do they fail? How humanlike do we expect them to become, and how soon do we need to worry about them surpassing us? Along the way, she introduces the dominant models of modern AI and machine learning, describing cutting-edge AI programs, their human inventors, and the historical lines of thought underpinning recent achievements. She meets with fellow experts such as Douglas Hofstadter, the cognitive scientist and Pulitzer Prize–winning author of the modern classic Gödel, Escher, Bach, who explains why he is “terrified” about the future of AI. She explores the profound disconnect between the hype and the actual achievements in AI, providing a clear sense of what the field has accomplished and how much further it has to go. Interweaving stories about the science of AI and the people behind it, Artificial Intelligence brims with clear-sighted, captivating, and accessible accounts of the most interesting and provocative modern work in the field, flavored with Mitchell’s humor and personal observations. This frank, lively book is an indispensable guide to understanding today’s AI, its quest for “human-level” intelligence, and its impact on the future for us all.
Lean AI
Author: Lomit Patel
Publisher: O'Reilly Media
ISBN: 1492059285
Category : Business & Economics
Languages : en
Pages : 237
Book Description
How can startups successfully scale customer acquisition and revenue growth with a Lean team? Out-of-the-box acquisition solutions from Facebook, Google, and others provide a good start, but the companies that can tailor those solutions to meet their specific needs, objectives, and goals will come out winners. But that hasn’t been an easy task—until now. With this practical book, author Lomit Patel shows you how to use AI and automation to provide an operational layer atop those acquisition solutions to deliver amazing results for your company. You’ll learn how to adapt, customize, and personalize cross-channel user journeys to help your company attract and retain customers—to usher in the new age of Autonomous Marketing. Learn how AI and automation can support the customer acquisition efforts of a Lean Startup Dive into Customer Acquisition 3.0, an initiative for gaining and retaining customers Explore ways to use AI for marketing purposes Understand the key metrics for determining the growth of your startup Determine the right strategy to foster user acquisition in your company Manage the increased complexity and risk inherent in AI projects
Publisher: O'Reilly Media
ISBN: 1492059285
Category : Business & Economics
Languages : en
Pages : 237
Book Description
How can startups successfully scale customer acquisition and revenue growth with a Lean team? Out-of-the-box acquisition solutions from Facebook, Google, and others provide a good start, but the companies that can tailor those solutions to meet their specific needs, objectives, and goals will come out winners. But that hasn’t been an easy task—until now. With this practical book, author Lomit Patel shows you how to use AI and automation to provide an operational layer atop those acquisition solutions to deliver amazing results for your company. You’ll learn how to adapt, customize, and personalize cross-channel user journeys to help your company attract and retain customers—to usher in the new age of Autonomous Marketing. Learn how AI and automation can support the customer acquisition efforts of a Lean Startup Dive into Customer Acquisition 3.0, an initiative for gaining and retaining customers Explore ways to use AI for marketing purposes Understand the key metrics for determining the growth of your startup Determine the right strategy to foster user acquisition in your company Manage the increased complexity and risk inherent in AI projects