E-Book, Englisch, 798 Seiten
Bonaccorso Mastering Machine Learning Algorithms
2. Auflage 2020
ISBN: 978-1-83882-191-3
Verlag: De Gruyter
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)
Expert techniques for implementing popular machine learning algorithms, fine-tuning your models, and understanding how they work
E-Book, Englisch, 798 Seiten
ISBN: 978-1-83882-191-3
Verlag: De Gruyter
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)
No detailed description available for "Mastering Machine Learning Algorithms".
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken Datenbankdesign & Datenbanktheorie
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Algorithmen & Datenstrukturen
- Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Informationsarchitektur
- Mathematik | Informatik EDV | Informatik Informatik Theoretische Informatik
Weitere Infos & Material
Table of Contents - Machine Learning Model Fundamentals
- Loss functions and Regularization
- Introduction to Semi-Supervised Learning
- Advanced Semi-Supervised Classifiation
- Graph-based Semi-Supervised Learning
- Clustering and Unsupervised Models
- Advanced Clustering and Unsupervised Models
- Clustering and Unsupervised Models for Marketing
- Generalized Linear Models and Regression
- Introduction to Time-Series Analysis
- Bayesian Networks and Hidden Markov Models
- The EM Algorithm
- Component Analysis and Dimensionality Reduction
- Hebbian Learning
- Fundamentals of Ensemble Learning
- Advanced Boosting Algorithms
- Modeling Neural Networks
- Optimizing Neural Networks
- Deep Convolutional Networks
- Recurrent Neural Networks
- Auto-Encoders
- Introduction to Generative Adversarial Networks
- Deep Belief Networks
- Introduction to Reinforcement Learning
- Advanced Policy Estimation Algorithms