Introduction to Automated Machine Learning (AutoML)
A

Introduction to Automated Machine Learning (AutoML)

Mathematics
AutoML machine learning hyperparameter optimization Bayesian optimization automated algorithms beginner guide research methods
Author
Frank Hutter, Lars Kotthoff, Joaquin Vanschoren
Publisher
DMK Press
Year
2023
Language
Russian
216
Rate this book

To read the book, log in / register

Preview fragment

Similar books

Machine Learning Without the Fluff

Machine Learning Without the Fluff

Andrey Burkov

Meta-learning. Applications in AutoML and Data Science

Meta-learning. Applications in AutoML and Data Science

Pavel Brazdil, Jan van Rijn, Carlos Soares, Joaquin Vanschoren

Bayesian models of perception and action. A modern perspective on brain functioning principles.

Bayesian models of perception and action. A modern perspective on brain functioning principles.

Wei Ji Ma, Conrad Kording, Daniel Goldreich

Shalev-Shwartz S., Ben-David S. - Understanding Machine Learning: From Theory to Algorithms - 2019

Shalev-Shwartz S., Ben-David S. - Understanding Machine Learning: From Theory to Algorithms - 2019

Sh. Shalev-Shwartz, Sh. Ben-David

Machine Learning. The science and art of building algorithms that extract knowledge from data.

Machine Learning. The science and art of building algorithms that extract knowledge from data.

Peter Flach

Machine Learning: Fundamentals, Algorithms, and Practical Applications

Machine Learning: Fundamentals, Algorithms, and Practical Applications

Jeremy Watt, Reza Borhani, Aggelos K. Katsaggelos

Machine Learning. System Design from Idea to Implementation

Machine Learning. System Design from Idea to Implementation

Valery Babushkin, Arseniy Kravchenko

Pyomo. Optimization Modeling in Python

Pyomo. Optimization Modeling in Python

Michael L. Bynum, Gabriel A. Hackebeil, William E. Hart, Carl D. Laird, Bethany L. Nicholson, John D. Siirola, Jean-Paul Watson, David L. Woodruff

Deep Learning from a Practitioner's Perspective

Deep Learning from a Practitioner's Perspective

Josh Patterson, Adam Gibson

Machine Learning for Business and Marketing

Machine Learning for Business and Marketing

Ilya Katsov