Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Computer Engineering Machine Learning and Neural Networks: A Computer Engineering Perspective

Computer Engineering Machine Learning and Neural Networks: A Computer Engineering Perspective

Chen, Yiran
Li, Hai
Yang, Huanrui

Hardcover

Technology & EngineeringGeneral Computers

Currently unavailable to order

ISBN10: 3032209781
ISBN13: 9783032209788
Publisher: Springer
Published: May 24 2026
Pages: 312
Weight: 1.61
Height: 0.82 Width: 6.48 Depth: 9.35
Language: English

This is the first textbook focusing on practicality of machine learning (ML) and deep neural networks (DNN), by introducing methods that enable engineering applications of ML and DNN models. The authors describe many methodologies that are widely used in designing, training, and deploying of these models and discuss their applicability under various contexts. Coverage begins with the basic knowledge of machine learning and deep neural networks and their applications in solving practical engineering problems. It then proceeds through a series of computer engineering methods commonly used in developing machine learning and deep neural network models. The book also explains how to improve the training and inference performance in terms of model accuracy, size, runtime, etc. by considering various requirements and availability of data in the applications. Techniques that are widely adopted in both industry and academia are discussed. Tutorials and projects designed to practice the introduced techniques are provided using popular development frameworks of machine learning.

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