Machine learning
by Ethem Alpaydin
Alpaydin's accessible primer on machine learning as 'the new AI' — algorithms that learn from data to power voice recognition and driverless cars.
"Machine learning is the basis of the new approach in computing where we do not write programs but collect data to learn algorithms automatically".
Editorial Summary
Özyegin University professor Ethem Alpaydin offers a concise overview of machine learning for the general reader in this MIT Press Essential Knowledge series volume. The book positions machine learning as the basis of a new approach in computing where we do not write programs but collect data, learning algorithms for tasks automatically from data. Alpaydin describes the basics of machine learning and applications including pattern recognition, artificial neural networks inspired by the human brain, algorithms for customer segmentation and recommendations, and reinforcement learning where autonomous agents maximize reward and minimize penalty. The author then considers future directions for machine learning and data science, discussing ethical and legal implications for data privacy and security. This accessible introduction covers applications from recommendation systems and face recognition to driverless cars, explaining how machine learning underlies technologies we use daily.
Perspective
"Machine Learning makes the field feel like an extension of common sense — Alpaydin's conciseness is a feature, not a limitation, giving readers who want orientation rather than depth exactly what they need to engage intelligently with the topic. The distinctive contribution is the MIT Press Essential Knowledge format itself: Alpaydin writes for a reader who wants to understand what machine learning actually is without being talked down to or buried in mathematics. Anyone beginning their AI reading journey, or anyone who has been nodding along to ML discussions without a solid foundation, will find this the fastest legitimate onramp."
Matched by concept and theme
