Artificial Intelligence Programming with Python: From Zero to Hero

Length: 720 pages
Edition: 1
Language: English
Publisher: Wiley
Publication Date: 2022-03-29
ISBN-10: 1119820863
ISBN-13: 9781119820864
Sales Rank: #3425407 (See Top 100 Books)

Artificial Intelligence, or AI, is no doubt one of the hottest buzz words at the moment. AI has penetrated into many aspects of our lives. To know AI and to be able to use AI will bring enormous benefits to our work and life. However, to learn AI is a daunting task for many people, largely due to the complex mathematics and sophisticated coding. This book aims to demystify AI and teach readers about AI from scratch, by using simple, plain, languages and simple, illustrative, code examples. This book is divided into three parts.

In part one, readers will follow an easy to read introduction about AI, including the history, the types of AI, the current status and possible future trend. It then introduces Python, A widely used programming tool for AI. In part two, we introduce Machine Learning aspect of AI, topics include classifications, regressions, and Clustering. It also includes the most popular Reinforcement Learning. In part three, it introduces Deep Learning aspect of AI, topics include Image Classifications, Transfer Learning, Recurrent Neural Network, and the latest Generative Adversarial Networks. It also includes the state of the art of GPU, TPU, cloud computing and edge computing.

This book is packed with interesting and exciting examples such as pattern recognitions, image classifications, face recognition (most controversial), age and gender detection, voice/speech recognition, chatbot, natural language processing, translation, sentiment analysis, predictive maintenance, finance and stock price analysis, sales prediction, customer segmentation, biomedical data analysis and much more.

Cover
Table of Contents
Title Page
Preface
    Why Buy This Book
    How This Book Is Organized
    Example Code
    Who This Book Is For
    What This Book Is Not For
    What You Need
Part I: Introduction
    CHAPTER 1: Introduction to AI
        1.1 What Is AI?
        1.2 The History of AI
        1.3 AI Hypes and AI Winters
        1.4 The Types of AI
        1.5 Edge AI and Cloud AI
        1.6 Key Moments of AI
        1.7 The State of AI
        1.8 AI Resources
        1.9 Summary
        1.10 Chapter Review Questions
    CHAPTER 2: AI Development Tools
        2.1 AI Hardware Tools
        2.2 AI Software Tools
        2.3 Introduction to Python
        2.4 Python Development Environments
        2.4 Getting Started with Python
        2.5 AI Datasets
        2.6 Python AI Frameworks
        2.7 Summary
        2.8 Chapter Review Questions
Part II: Machine Learning and Deep Learning
    CHAPTER 3: Machine Learning
        3.1 Introduction
        3.2 Supervised Learning: Classifications
        3.3 Supervised Learning: Regressions
        3.4 Unsupervised Learning
        3.5 Semi-supervised Learning
        3.6 Reinforcement Learning
        3.7 Ensemble Learning
        3.8 AutoML
        3.9 PyCaret
        3.10 LazyPredict
        3.11 Summary
        3.12 Chapter Review Questions
    CHAPTER 4: Deep Learning
        4.1 Introduction
        4.2 Artificial Neural Networks
        4.3 Convolutional Neural Networks
        4.4 Recurrent Neural Networks
        4.5 Transformers
        4.6 Graph Neural Networks
        4.7 Bayesian Neural Networks
        4.8 Meta Learning
        4.9 Summary
        4.10 Chapter Review Questions
Part III: AI Applications
    CHAPTER 5: Image Classification
        5.1 Introduction
        5.2 Classification with Pre-trained Models
        5.3 Classification with Custom Trained Models: Transfer Learning
        5.4 Cancer/Disease Detection
        5.5 Federated Learning for Image Classification
        5.6 Web-Based Image Classification
        5.7 Image Processing
        5.8 Summary
        5.9 Chapter Review Questions
    CHAPTER 6: Face Detection and Face Recognition
        6.1 Introduction
        6.2 Face Detection and Face Landmarks
        6.3 Face Recognition
        6.4 Age, Gender, and Emotion Detection
        6.5 Face Swap
        6.6 Face Detection Web Apps
        6.7 How to Defeat Face Recognition
        6.8 Summary
        6.9 Chapter Review Questions
    CHAPTER 7: Object Detections and Image Segmentations
        7.1 Introduction
        7.2 Object Detections with Pretrained Models
        7.3 Object Detections with Custom Trained Models
        7.4 Object Tracking
        7.5 Image Segmentation
        7.6 Background Removal
        7.7 Depth Estimation
        7.8 Augmented Reality
        7.9 Summary
        7.10 Chapter Review Questions
    CHAPTER 8: Pose Detection
        8.1 Introduction
        8.2 Hand Gesture Detection
        8.3 Sign Language Detection
        8.4 Body Pose Detection
        8.5 Human Activity Recognition
        8.6 Summary
        8.7 Chapter Review Questions
    CHAPTER 9: GAN and Neural-Style Transfer
        9.1 Introduction
        9.2 Generative Adversarial Network
        9.3 Neural-Style Transfer
        9.4 Adversarial Machine Learning
        9.5 Music Generation
        9.6 Summary
        9.7 Chapter Review Questions
    CHAPTER 10: Natural Language Processing
        10.1 Introduction
        10.2 Text Summarization
        10.3 Text Sentiment Analysis
        10.4 Text/Poem Generation
        10.5 Text to Speech and Speech to Text
        10.6 Machine Translation
        10.7 Optical Character Recognition
        10.8 QR Code
        10.9 PDF and DOCX Files
        10.10 Chatbots and Question Answering
        10.11 Summary
        10.12 Chapter Review Questions
    CHAPTER 11: Data Analysis
        11.1 Introduction
        11.2 Regression
        11.3 Time-Series Analysis
        11.4 Predictive Maintenance Analysis
        11.5 Anomaly Detection and Fraud Detection
        11.6 COVID-19 Data Visualization and Analysis
        11.7 KerasClassifier and KerasRegressor
        11.8 SQL and NoSQL Databases
        11.9 Immutable Database
        11.10 Summary
        11.11 Chapter Review Questions
    CHAPTER 12: Advanced AI Computing
        12.1 Introduction
        12.2 AI with Graphics Processing Unit
        12.3 AI with Tensor Processing Unit
        12.4 AI with Intelligence Processing Unit
        12.5 AI with Cloud Computing
        12.6 Web-Based AI
        12.7 Packaging the Code
        12.8 AI with Edge Computing
        12.9 Create a Mobile AI App
        12.10 Quantum AI
        12.11 Summary
        12.12 Chapter Review Questions
Index
Copyright
Dedication
About the Author
About the Technical Editors
Acknowledgments
End User License Agreement