Artificial Intelligence in Business Explained
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- Comprehensive Ai Introduction
- Machine and Deep Learning, Nlp, Computer Vision
- Ai’s Potential Everyday Applications
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About Artificial Intelligence in Business Explained
Introducing our comprehensive guide to Artificial Intelligence for beginners. From machine learning and natural language processing to computer vision and robotics, this book covers all the key concepts and techniques used in modern AI.
You will also learn about expert systems, neural networks, and deep learning, and how these technologies are used to evaluate and improve the performance of AI models.
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Table of contents 
- Introduction to Artificial Intelligence
- Different Types of Artificial Intelligence
- The history of AI
- AI techniques and algorithms
- Machine learning
- Natural language processing
- Part of speech tagging
- Named entity recognition
- Sentiment analysis
- Language Translation
- Text summarization
- Computer vision
- Image processing
- Feature extraction
- Object recognition
- Facial recognition
- Scene understanding
- Robotics
- Consumer robots
- Expert systems
- Neural networks
- Deep learning
- Advantages of deep learning
- Evaluating and improving the performance of artificial intelligence models
- Artificial intelligence vs. Machine learning vs. Deep learning
- Power struggle in AI: who controls technology?
- Debate on AI creativity: can machines be creative?
- Overcoming the shortage of AI experts in the talent gap
- The paradox of AI transparency: can we make AI explain itself?
- AI and the future of human-computer interaction
- The ethics of AI and robot rights
- AI and the philosophy of mind
- The AI apocalypse: risks and dangers of advanced AI
- How can you make your everyday life easier with the power of AI?
- Personal assistants
- Smart home devices
- Transportation
- Healthcare
- Education
- Customer service
- Legal and regulatory framework for AI
- Enhancing human capabilities with AI
- Conclusion
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Covers a lot of important AI topics in a beginner-friendly way. That said, some explanations could have been clearer, especially for complex areas like deep learnin
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