Machine learning
Artificial intelligence : a guide for thinking humans
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 ...
- Vị trí lưu trữ: 03 Quang Trung
- Tổng sách: 5
- Đang rỗi: 5
1. Why we are interested in machine learning; 2. Machine learning, statistics and data analytics; 3. Pattern recognition; 4. Neural networks and deep learning; 5. Learning clusters and recommendations; 6. Learning to take actions; 7. Where do we go from here?.
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The book explores case studies of countries that have successfully managed to stem corruption, and the roles that the judicial system, auditors, ombudspersons, and the media can play in halting corruption. However, Rotberg argues, the essential ingredient to fighting corruption is a leader with the ...
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Presenting to Introduction to deep learning. Conceptual foundations. Neural networks: the building blocks of deep learning. A brief history of deep learning. Convolutional and recurrent networks. Learning functions. The future of deep learning.
- Vị trí lưu trữ: 03 Quang Trung
- Tổng sách: 3
- Đang rỗi: 3