Karim / Kumar N Machine Learning with Scala Quick Start Guide

Leverage popular machine learning algorithms and techniques and implement them in Scala
1. Auflage 2019
ISBN: 978-1-78934-541-4
Verlag: De Gruyter
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 220 Seiten

No detailed description available for "Machine Learning with Scala Quick Start Guide".

Autoren/Hrsg.

Karim, Md. Rezaul

Kumar N, Ajay

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Theoretische Informatik
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Datenbankdesign & Datenbanktheorie
• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Informationsarchitektur
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Automatische Datenerfassung, Datenanalyse

Inhaltsverzeichnis

Table of Contents - Introduction to Machine Learning with Scala
- Scala for Regression Analysis
- Scala for Learning Classification
- Scala for Tree-based Ensemble Techniques
- Scala for Dimensonality Reduction and Clustering
- Scala for Recommender System
- Introduction to Deep Learning with Scala

Über Autor(innen)

Karim Md. Rezaul:
Md. Rezaul Karim is a researcher, author, and data science enthusiast with a strong computer science background, coupled with 10 years of research and development experience in machine learning, deep learning, and data mining algorithms to solve emerging bioinformatics research problems by making them explainable. He is passionate about applied machine learning, knowledge graphs, and explainable artificial intelligence (XAI). Currently, he is working as a research scientist at Fraunhofer FIT, Germany. He is also a PhD candidate at RWTH Aachen University, Germany. Before joining FIT, he worked as a researcher at the Insight Centre for Data Analytics, Ireland. Previously, he worked as a lead software engineer at Samsung Electronics, Korea.Kumar N Ajay:
Ajay Kumar N has experience in big data, and specializes in cloud computing and various big data frameworks, including Apache Spark and Apache Hadoop. His primary language of choice is Python, but he also has a special interest in functional programming languages such as Scala. He has worked extensively with NumPy, pandas, and scikit-learn, and often contributes to open source projects related to data science and machine learning.