Machine Learning for Computer Scientists and Data Analysts - From an Applied Perspective (Hardcover, 1st ed. 2022)

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.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Release date:	July 2022
Authors:	Setareh Rafatirad • Houman Homayoun • Zhiqian Chen • Sai Manoj Pudukotai Dinakarrao
Dimensions:	235 x 155 x 30mm (L x W x T)
Format:	Hardcover
Pages:	458
Edition:	1st ed. 2022
ISBN-13:	978-3-03-096755-0
Categories:	Books > Professional & Technical > Energy technology & engineering > Electrical engineering > General Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Circuits & components Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
LSN:	3-03-096755-7
Barcode:	9783030967550

Is the information for this product incomplete, wrong or inappropriate? Let us know about it.

Does this product have an incorrect or missing image? Send us a new image.

Is this product missing categories? Add more categories.

Review This Product

No reviews yet - be the first to create one!