Dangeti Statistics for Machine Learning

Techniques for exploring supervised, unsupervised, and reinforcement learning models with Python and R
1. Auflage 2017
ISBN: 978-1-78829-122-4
Verlag: De Gruyter
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 442 Seiten

No detailed description available for "Statistics for Machine Learning".

Autoren/Hrsg.

Dangeti, Pratap

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Datenbankdesign & Datenbanktheorie
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Automatische Datenerfassung, Datenanalyse
• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Informationsarchitektur
• Mathematik | Informatik EDV | Informatik Business Application Mathematische & Statistische Software

Inhaltsverzeichnis

Table of Contents - Journey from Statistics to Machine Learning

- Parallelism of Statistics and Machine Learning
- Logistic Regression vs. Random Forest

- Tree-Based Machine Learning models
- K-Nearest Neighbors & Naïve Bayes

- Support Vector Machines & Neural Networks
- Recommendation Engines

- Unsupervised Learning

- Reinforcement Learning

Über Autor(innen)

Dangeti Pratap:

Pratap Dangeti develops machine learning and deep learning solutions for structured, image, and text data at TCS, analytics and insights, innovation lab in Bangalore. He has acquired a lot of experience in both analytics and data science. He received his master's degree from IIT Bombay in its industrial engineering and operations research program. He is an artificial intelligence enthusiast. When not working, he likes to read about next-gen technologies and innovative methodologies.