Buch, Englisch, 196 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 500 g
Reihe: EAI/Springer Innovations in Communication and Computing
Buch, Englisch, 196 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 500 g
Reihe: EAI/Springer Innovations in Communication and Computing
ISBN: 978-3-030-93087-5
Verlag: Springer
This book is a comprehensive, hands-on guide to the basics of data mining and machine learning with a special emphasis on supervised and unsupervised learning methods. The book lays stress on the new ways of thinking needed to master in machine learning based on the Python, R, and Java programming platforms. This book first provides an understanding of data mining, machine learning and their applications, giving special attention to classification and clustering techniques. The authors offer a discussion on data mining and machine learning techniques with case studies and examples. The book also describes the hands-on coding examples of some well-known supervised and unsupervised learning techniques using three different and popular coding platforms: R, Python, and Java. This book explains some of the most popular classification techniques (K-NN, Naïve Bayes, Decision tree, Random forest, Support vector machine etc,) along with the basic description of artificial neural network and deep neural network. The book is useful for professionals, students studying data mining and machine learning, and researchers in supervised and unsupervised learning techniques.
Zielgruppe
Professional/practitioner
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
- Mathematik | Informatik EDV | Informatik Informatik Bildsignalverarbeitung
- Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Computer Vision
Weitere Infos & Material
Table of Content
Prefaces
Declaration
Acknowledgement
About AuthorsChapter-1: Introduction to Data Mining & Knowledge Discovery
Sanjay Chakraborty, SK Hafizul Islam, Debabrata Samanta
Chapter-2: A Brief Concept on Machine LearningSanjay Chakraborty, SK Hafizul Islam, Debabrata Samanta
Chapter-3: Supervised Learning based Data Classification and Incremental Clustering
Sanjay Chakraborty, SK Hafizul Islam, Debabrata Samanta
Chapter-4: Data Classification and Incremental Clustering using Unsupervised Learning
Sanjay Chakraborty, SK Hafizul Islam, Debabrata Samanta
Chapter-5: Research Intention towards Incremental Clustering
Sanjay Chakraborty, SK Hafizul Islam, Debabrata Samanta
Chapter-6: Applications and Trends in Data Mining & Machine Learning
Sanjay Chakraborty, SK Hafizul Islam, Debabrata Samanta
Chapter 7: Feature subset selection techniques with Machine LearningSanjay Chakraborty, SK Hafizul Islam, Debabrata Samanta
Chapter 8: Data Mining Based variant subsets features
Sanjay Chakraborty, SK Hafizul Islam, Debabrata Samanta
Index




