Litgu.ru - Литературный Гуру

I. Preface
II. Who is this Book for?
1. Introduction
1.1 Background
1.2 What is Artificial Intelligence (AI)?
1.3 AI is not a Robot
1.4 The AI Race
1.5 AI & The Global Economy
1.6 Why Should You Care?
1.7 What AI Cannot Do Now?
2. Industry 4.0
2.1 The 4th Industrial Revolution
2.2 What is the 4th Industrial Revolution ?
2.3 Robotic Process Automation (RPA)
2.4 Blockchain Technology
2.5 Internet of Things
2.6 Robotics
2.7 Smart City
2.8 Cyber Security
2.9 Cloud Computing
2.10 Cognitive Computing
2.11 Quantum Computation
2.12 Digital Reality (DR)
3. AI 101
3.1 History: The Evolution of AI
3.2 Enablers: Why AI is Booming Now?
3.3 Types of Artificial Intelligence
3.3.1 Stages of development
1.3.2 Functionality-based AI Types
1.3.3 The 4 AI Applications
1.3.4 Technique-based AI
3.4 How it Works?
3.5 Why You need AI?
3.6 Social Robots
3.7 The AI Debate
4. Data
4.1 What is Data?
4.2 Types of Data
4.3 Why Data is the Fuel?
4.4 What is Big Data?
4.5 The 5Vs
4.6 Big Data Life Cycle
4.7 Data Collection
4.8 Data Management & Analytics
4.9 Hadoop Framework
4.10 AI & dаta: Common Misconceptions
4.11 Additional Key Concepts
4.12 Big Data : Risks and Ethics
5. Introduction to Machine Learning
5.1 What is Machine Learning
5.2 Basic Concepts
5.3 How Machines Learn ?
5.4 Types of Machine Learning
6.Supervised Learning
6.1 What is Supervised Learning?
6.2 Types of Machine Learning
6.3 What is Classification ?
6.4 Classification Algorithms
6.4.1 The K-Nearest Neighbor Classifier
6.4.2 Support Vector Machines
6.4.3 Linear Classifiers: Logistic Regression & Naïve Bayes
6.4.4 Decision Tree
6.4.5 Random Forest
6.4.6 Neural Network
6.5 Examples of Classification
6.6 What is Regression?
6.6.1 Understanding Linear Regression
6.6.2 Learning Linear Regression
6.6.3 Visualizing Linear Regression
6.6.4 Applying Regression to Label Predictions
6.7 Regression Algorithms
6.7.1 Simple Linear Regression Model
6.7.2 Lasso Regression
6.7.3 Support Vector Machines
6.8 Examples of Regression
7. Unsupervised Learning
7.1 What is Unsupervised Learning?
7.1.2 Types of Unsupervised Learning
7.2 What is Clustering ?
7.3 Types of Clustering
7.3.1 Methods of Clustering
7.3.2 Types of Clustering
7.4 Dimensionality Reduction
7.4.1 What is Dimensionality Reduction?
7.4.2 Methods of Dimensionality Reduction
7.4.3 Pros and Cons of Dimensionality Reduction
7.5 Examples of Dimensionality Reduction
8. Reinforcement Leaning
8.1 What is Reinforcement Learning?
8.1.1 Difference between Reinforcement Learning and Supervised Learning
8.1.2 How Reinforcement Learning Works
8.2 Reinforcement Learning Algorithms
8.2.1 Classification of Reinforcement Learning Algorithms
8.2.2 Types of Reinforcement Learning
8.2.3 Learning Models of Reinforcement Learning
8.3 Applications of Reinforcement Learning
8.3.1 Self-Driving Cars
8.3.2 Traffic Control
8.3.3 Robotics
8.3.4 Web System Configuration
8.3.5 Chemistry
8.3.6 Personalized Recommendations
8.3.7 Games
9. Deep Learning
9.1 The Fundamentals of Artificial Neural Networks
9.2 The Construction of Artificial Neural Networks
9.2.1 Weights and Inputs
9.2.2 Activations and Outputs
9.2.3 Neuron Activation
9.2.4 The Perceptron
9.2.5 Networking Neurons
9.2.6 Comparing the AI Brain and the Human Brain
9.3 What is Deep Learning ?
9.4 Deep Learning vs Machine Learning
9.5 Types of Deep Learning
9.5.1 Feedforward Neural Networks
9.5.2 Backpropagation
9.6 Convolutional Neural Networks
9.7 Recurrent Neural Networks (RNN)
9.8 Generative Adversarial Networks (GAN)
10. The Machine Learning Process Framework
10.1 The Machine Learning Process Framework
10.2 Problem Formulation
10.3 Data Preprocessing
10.4 Feature Engineering
10.5 Data Splitting
10.6 ML Algorithm Selection
10.7 Model Training
10.8 Model Evaluation
10.9 Model Improvement
10.10 Model Deployment
11. AI Capabilities
11.1 Speech Recognition
11.2 Natural Language Processing
11.2.1 Example
11.3 Computer Vision
11.3.1 What is it?
11.3.2 How Does it Work?
11.3.3 Industry Applications
11.4 Drones, Autonomous Vehicles & Intelligent Robotics
11.4.1 What is it?
11.4.2 How does it work?
11.2.3 The DARPA Challenge
11.2.4 Valkyrie
11.5 Predictive Analytics
11.5.1 What is it?
11.5.2 How does it work?
11.5.3 Example
12. Industry-Based AI Applications
12.1 AI in Education
12.1.1 Student Universal Access
12.1.2 Automate Administrative Tasks
12.1.3 Out-of-School Tutoring and Support
12.2 AI in Healthcare
12.2.1 Staying Healthy
12.2.2 Early Detection
12.2.3 Diagnosis
12.2.4 Improve Decision-Making
12.2.5 Treatment
12.2.6 End-of-Life Care
12.2.7 Research
12.2.8 Training
12.3 AI in Meteorology
12.4 AI in Business Analysis
12.5 AI in Communication
12.6 AI in Industrial Operations
12.7 AI in Pharmaceuticals
12.8 AI in Property Management
12.8.1 Automated Property Management
12.8.2 The Recommendation System
12.8.3 Virtual Assistants
12.9 AI in Financial Services
12.10 AI in Security
12.10.1 AI and Security Applications
12.11 AI in Marketing & Retail
12.12 AI in E-Commerce
12.12.1 Chatbots & Virtual Assistants
12.12.2 Intelligent Product Recommendations
12.12.3 Personalization Services
12.13 AI in Oil & Gas
12.14 AI in Space
12.14.1 Space Exploration
12.14.2 Astronaut Assistants
12.14.3 Applications of AI in Space
12.15 AI in Agriculture
12.16 AI in Politics & Economics
12.17 AI in Logistics & Transportation
12.17.1 Autonomous Vehicles
13. Responsible AI
13.1 AI Governance
13.2 AI Ethics
13.3 Human-AI Collaboration
13.4 AI & Society
13.5 Society-Related AI Projects
13.6 Singularity
13.7 Our Responsibility to Our Children
14. The Future of Jobs
14.1 AI and Job Markets
14.2 What Jobs AI Will Replace
14.3 What Jobs AI Won’t Replace
14.5 The Most In-Demand Future Jobs
15. The AI Economy
15.1 Latest Trends in AI
15.1.1 Computer Vision
15.1.2 Generative Adversarial Networks
15.1.3 Natural Language Processing
15.1.4 Training & Deployment of Powerful Models
15.2 AI: Economic Potential
15.3 The AI Patent Race
15.4 AI & Policy Implications
15.4.1 Policy Implications
15.5 Economic and Societal Cost
15.6 Taxing Robots & Universal Basic Income (UBI)
15.6.1 Taxing Robots
15.6.2 Universal Basic Income (UBI)
15.7 Maximizing the AI Benefits
15.8 Private vs. Government Sector
15.9 The AI Start-Up Economy
16. Business AI
16.1 What Is In It For Enterprises?
16.2 Why You Need to Adopt AI Fast?
16.3 How to Build Your AI Strategy ?
16.4 The Agile Approach
16.5 Methodologies & Tools
16.6 Best Practices in Developing AI
17. Conclusion
Bibliography
Index