Applied machine learning and AI for engineers : solve business problems that can't be solved algorithmically / Jeff Prosise ; foreword by Adam Prosise.
Material type: TextPublisher: Sebastopol, CA : O'Reilly Media, 2022Copyright date: ©2023Edition: First editionDescription: xx, 400 pages : illustrations (some color) ; 24 cmContent type:- text
- unmediated
- volume
- 9781492098058
- 1492098051
- Applied machine learning and artificial intelligence for engineers
- 006.31 PRO 23 24733
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Books | COMSATS University Wah Campus | 006.31 PRO 24733 (Browse shelf(Opens below)) | Available | 10004000024733 |
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Includes bibliographical references and index.
Part 1. Machine learning with Schikit-learn. Machine learning -- Regression models -- Classification models -- Text classification -- Support vector machines -- Principal component analysis -- Operationalizing machine learning models -- Part 2. Deep learning with Keras and TensorFlow. Deep learning -- Neural networks -- Image classification with convolutional neural networks -- Face detection and recognition -- Object detection -- Natural language processing -- Azure cognitive services.
While many introductory guides to AI are calculus books in disguise, this one mostly eschews the math. Instead, author Jeff Prosise helps engineers and software developers build an intuitive understanding of AI to solve business problems. Need to create a system to detect the sounds of illegal logging in the rainforest, analyze text for sentiment, or predict early failures in rotating machinery? This practical book teaches you the skills necessary to put AI and machine learning to work at your company.
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