Understanding Machine Learning
Understanding Machine Learning Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The book provides an extensive theoretical account of the…
Specifikacia Understanding Machine Learning
Understanding Machine Learning
Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The book provides an extensive theoretical account of the fundamental ideas underlying machine learning and the mathematical derivations that transform these principles into practical algorithms. The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a principled way.
These include a discussion of the computational complexity of learning and the concepts of convexity and stability; important algorithmic paradigms including stochastic gradient descent, neural networks, and structured output learning; and emerging theoretical concepts such as the PAC-Bayes approach and compression-based bounds. Following a presentation of the basics of the field, the book covers a wide array of central topics that have not been addressed by previous textbooks. Designed for an advanced undergraduate or beginning graduate course, the text makes the fundamentals and algorithms of machine learning accessible to students and non-expert readers in statistics, computer science, mathematics, and engineering.
Understanding Machine Learning
Machine Learning
Machine Learning
Machine Learning
Machine Learning
Machine Learning
MACHINE LEARNING
Machine Learning Algorithms
Graph Machine Learning
Machine Learning Refined
Python Machine Learning
Python Machine Learning
Python Machine Learning
Machine Learning Engineering
Programming Machine Learning
Introducing Machine Learning