Machine Learning Methods - Hang Li
-20% with code BOOKS
Shipping in 17-23 days
30-day return policy
This book provides a comprehensive and systematic introduction to the principal machine learning methods, covering both supervised and unsupervised learning methods. It discusses essential methods of classification and regression in supervised learning, such as decision trees, perceptrons, support vector machines, maximum entropy models, logistic regression models and multiclass classification, as well as m ... Full description
You May Also Like
TOP
Gödel, Escher, Bach: An Eternal Golden Braid
-20% with code BOOKS
In stock at our supplier
TOP
Empire of AI: Dreams and Nightmares in Sam Altmans OpenAI
-20% with code BOOKS
In stock at our supplier
TOP
AI Engineering: Building Applications with Foundation Models
-20% with code BOOKS
In stock at our supplier
TOP
The Pragmatic Programmer: journey to mastery, 20th Anniversary Edition, 2/e: your journey to mastery, 20th Anniversary Edition
-20% with code BOOKS
In stock at our supplier
TOP
The Rust Programming Language
Steve Klabnik, Carol Nichols, Chris Krycho
-20% with code BOOKS
In stock at our supplier
TOP
How Linux Works: What Every Superuser Should Know
-20% with code BOOKS
In stock at our supplier
TOP
Python Crash Course: A Hands-On, Project-Based Introduction to Programming
-20% with code BOOKS
In stock at our supplier
TOP
How To Think About AI: A Guide For The Perplexed
-20% with code BOOKS
In stock at our supplier
TOP
Slanted 47 Digital Tools: Slanted Magazine
-20% with code BOOKS
In stock at our supplier
TOP
The Art of Game Design: A Book of Lenses
-20% with code BOOKS
In stock at our supplier
TOP
Artificial Intelligence: A Modern Approach, Global Edition
-20% with code BOOKS
In stock at our supplier
TOP
CompTIA Security+ Certification Kit: Exam SY0-701
-20% with code BOOKS
In stock at our supplier
TOP
Automate the Boring Stuff with Python
-20% with code BOOKS
In stock at our supplier
TOP
Fundamentals of Software Architecture: A Modern Engineering Approach
-20% with code BOOKS
In stock at our supplier
TOP
Speak Data: Artists, Scientists, Thinkers, and Dreamers on How We Live Our Lives in Numbers
-20% with code BOOKS
In stock at our supplier
TOP
Hacking: The Art of Exploitation
-20% with code BOOKS
In stock at our supplier
TOP
Hackers. 25th Anniversary Edition: Heroes of the Computer Revolution
-20% with code BOOKS
In stock at our supplier
TOP
Deep Learning
Ian Goodfellow, Yoshua Bengio, Aaron Courville
-20% with code BOOKS
In stock at our supplier
TOP
Proofs from THE BOOK
Martin Aigner, Günter M. Ziegler
-20% with code BOOKS
In stock at our supplier
TOP
Mathematics for Machine Learning
Cheng Soon Ong, A. Aldo Faisal, Marc Peter Deisenroth
-20% with code BOOKS
In stock at our supplier
Description
This book provides a comprehensive and systematic introduction to the principal machine learning methods, covering both supervised and unsupervised learning methods. It discusses essential methods of classification and regression in supervised learning, such as decision trees, perceptrons, support vector machines, maximum entropy models, logistic regression models and multiclass classification, as well as methods applied in supervised learning, like the hidden Markov model and conditional random fields. In the context of unsupervised learning, it examines clustering and other problems as well as methods such as singular value decomposition, principal component analysis and latent semantic analysis. As a fundamental book on machine learning, it addresses the needs of researchers and students who apply machine learning as an important tool in their research, especially those in fields such as information retrieval, natural language processing and text data mining. In order to understand the concepts and methods discussed, readers are expected to have an elementary knowledge of advanced mathematics, linear algebra and probability statistics. The detailed explanations of basic principles, underlying concepts and algorithms enable readers to grasp basic techniques, while the rigorous mathematical derivations and specific examples included offer valuable insights into machine learning.
More Information
| Author | Hang Li |
|---|---|
| Publisher | Springer Nature Singapore |
| Release year | 2023 |
| Cover type | Hardcover |
| EAN | 9789819939169 |