Machine learning techniques provide cost-effective alternatives to traditional methods for extracting underlying relationships between information and data and for predicting future events by processing existing information to train models. Efficient Learning Machines explores the major topics of machine learning, including knowledge discovery, classifications, genetic algorithms, neural networking, kernel methods, and biologically-inspired techniques.
Authors synthetic approach weaves together the theoretical exposition, design principles, and practical applications of efficient machine learning. Their experiential emphasis, expressed in their close analysis of sample algorithms throughout the book, aims to equip engineers, students of engineering, and system designers to design and create new and more efficient machine learning systems. Readers of Efficient Learning Machines will learn how to recognize and analyze the problems that machine learning technology can solve for them, how to implement and deploy standard solutions to sample problems, and how to design new systems and solutions.
| Pages : | /Paperback 268 pages |
| Size : | PDF and ePub |
| Downloads: | 14 |
| Created: | 2020-08-29 |
| License: | CC BY 4.0 |
| Author(s): | Mariette Awad, Rahul Khanna |
Others related eBooks about Efficient Learning Machines: Theories, Concepts, and Applications for Engineers and System Designers
This open access book presents the first comprehensive overview of general methods in Automated Machine Learning (AutoML), collects descriptions of existing systems based on these methods, and discusses the first series of international challenges of AutoML systems.
TensorFlow, Google's library for large-scale machine learning, simplifies often-complex computations by representing them as graphs and efficiently mapping parts of the graphs to machines in a cluster or to the processors of a single machine.
This book presents fundamental machine learning concepts in an easy to understand manner b..., download free Machine Learning tutorial in PDF (348 pages) created by Miroslav Kubat .
Download free course Interpretable Machine Learning, pdf file on 312 pages by Christoph Molnar.
AI is transforming numerous industries. Machine Learning Yearning, a free ebook from Andre..., download free Machine Learning tutorial in PDF (118 pages) created by Andrew Ng .