Machine Learning for Computer Scientists and Data Analysts (PDF)
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This textbook introduces readers to the theoretical aspects of machine learning (ML) algorithms, starting from simple neuron basics, through complex neural networks, including generative adversarial neural networks and graph convolution networks. Most importantly, this book helps readers to understand the concepts of ML algorithms and enables them to develop the skills necessary to choose an apt ML algorithm for a problem they wish to solve. In addition, this book includes numerous case studies, ranging from simple time-series forecasting to object recognition and recommender systems using massive databases. Lastly, this book also provides practical implementation examples and assignments for the readers to practice and improve their programming capabilities for the ML applications.
Describes traditional as well as advanced machine learning algorithms;
Enables students to learn which algorithm is most appropriate for the data being handled;
Includes numerous, practical case-studies; implementation codes in Python available for readers;
Uses examples and exercises to reinforce concepts introduced and develop skills.
Setareh Rafatirad is an Associate Professor in Department of Information Sciences and Technology at George Mason University. She obtained her M.Sc. and PhD in Computer Science from University of California, Irvine in 2009 and 2012. Her research interest covers several areas including Big Data Analytics, Data Mining, Knowledge Discovery and Knowledge Representation, Image Understanding, Multimedia Information Retrieval, and Applied Machine Learning. Currently, she is actively supervising multiple research projects focused on applying ML and Deep Learning techniques on different domains including House Price Prediction, Malware Detection, and Emerging big data application benchmarking and characterization on heterogeneous architectures.
Houman Homayoun is anAssistant Professor in the Department of Electrical and Computer Engineering at George Mason University. He also
- Autoren: Setareh Rafatirad , Houman Homayoun , Zhiqian Chen , Sai Manoj Pudukotai Dinakarrao
- 2022, 1st ed. 2022, 458 Seiten, Englisch
- Verlag: Springer International Publishing
- ISBN-10: 3030967565
- ISBN-13: 9783030967567
- Erscheinungsdatum: 09.07.2022
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
- Dateiformat: PDF
- Größe: 12 MB
- Ohne Kopierschutz
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