Jeyaraman / Olsen / Wambugu Practical Machine Learning with R

Define, build, and evaluate machine learning models for real-world applications
1. Auflage 2019
ISBN: 978-1-83855-284-8
Verlag: De Gruyter
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 416 Seiten

No detailed description available for "Practical Machine Learning with R".

Autoren/Hrsg.

Jeyaraman, Brindha Priyadarshini

Olsen, Ludvig Renbo

Wambugu, Monicah

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Informationsarchitektur
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Datenbankdesign & Datenbanktheorie
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Neuronale Netzwerke

Inhaltsverzeichnis

Table of Contents - An Introduction to Machine Learning
- Data Cleaning and Pre-Processing
- Feature Engineering
- Introduction to neuralnet and Evaluation Methods
- Linear and Logistic Regression Models
- Unsupervised Learning

Über Autor(innen)

Jeyaraman Brindha Priyadarshini:

Brindha Priyadarshini Jeyaraman is a senior data scientist at AIDA Technologies. She has completed her M.Tech in knowledge engineering with a gold medal from the National University of Singapore. She has more than 10 years of work experience and she is an expert in understanding business problems, and designing and implementing solutions using machine learning. She has worked on several real data science projects in the insurance and finance domain.Olsen Ludvig Renbo:

Ludvig Renbo Olsen, BSc in Cognitive Science from Aarhus University, is the author of multiple R packages, such as groupdata2 and cvms. With 4 years of R and Python experience, including working as a machine learning researcher at the Danish startup UNSILO, he is passionate about creating tools and tutorials for students and scientists. Guided by Effective Altruism, he intends to positively impact the world through his career.Wambugu Monicah:

Monicah Wambugu is the lead Data Scientist at Loanbee, a financial technology company that offers micro-loans by leveraging on data, machine learning and analytics to perform alternative credit scoring. She is a graduate student at the School of Information at UC Berkeley Masters in Information Management and Systems. Monicah is particularly interested in how data science and machine learning can be used to design products and applications that respond to the behavioral and socio-economic needs of target audiences.