Machine Learning for Computer Scientists and Data Analysts: From an Applied Perspective (1st ed. 2022)
By: and and and
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- Synopsis
- 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.
- Copyright:
- 2022
Book Details
- Book Quality:
- Publisher Quality
- ISBN-13:
- 9783030967567
- Related ISBNs:
- 9783030967550
- Publisher:
- Springer International Publishing
- Date of Addition:
- 08/31/22
- Copyrighted By:
- The Editor
- Adult content:
- No
- Language:
- English
- Has Image Descriptions:
- No
- Categories:
- Nonfiction, Computers and Internet, Technology
- Submitted By:
- Bookshare Staff
- Usage Restrictions:
- This is a copyrighted book.
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