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Hands-on ML Projects with OpenCV

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Title: Hands-on ML Projects with OpenCV
Description: This book is an in-depth guide that merges machine learning techniques with OpenCV, the most popular computer vision library, using Python. The book introduces fundamental concepts in machine learning and computer vision, progressing to practical implementation with OpenCV. Concepts related to image preprocessing, contour and thresholding techniques, motion detection and tracking are explained in a step-by-step manner using code and output snippets. Hands-on projects with real-world datasets will offer you an invaluable experience in solving OpenCV challenges with machine learning. It's an ultimate guide to explore areas like deep learning, transfer learning, and model optimization, empowering readers to tackle complex tasks. Every chapter offers practical tips and tricks to build effective ML models. By the end, you would have mastered and applied ML concepts confidently to real-world computer vision problems and will be able to develop robust and accurate machine-learning models for diverse applications. Whether you are new to machine learning or seeking to enhance your computer vision skills, This book is an invaluable resource for mastering the integration of machine learning and computer vision using OpenCV and Python.
Authors: Mugesh S.
Resource Type: eBook.
Subjects: Computers, Computer vision, Artificial intelligence, Neural networks (Computer science), Electronic books, Pattern recognition systems
Categories: COMPUTERS / Artificial Intelligence / General
Database: eBook Collection (EBSCOhost)
FullText Links:
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  – Type: ebook-epub
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  Availability: 0
Header DbId: nlebk
DbLabel: eBook Collection (EBSCOhost)
An: 3677962
RelevancyScore: 1116
AccessLevel: 6
PubType: eBook
PubTypeId: ebook
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  Data: This book is an in-depth guide that merges machine learning techniques with OpenCV, the most popular computer vision library, using Python. The book introduces fundamental concepts in machine learning and computer vision, progressing to practical implementation with OpenCV. Concepts related to image preprocessing, contour and thresholding techniques, motion detection and tracking are explained in a step-by-step manner using code and output snippets. Hands-on projects with real-world datasets will offer you an invaluable experience in solving OpenCV challenges with machine learning. It's an ultimate guide to explore areas like deep learning, transfer learning, and model optimization, empowering readers to tackle complex tasks. Every chapter offers practical tips and tricks to build effective ML models. By the end, you would have mastered and applied ML concepts confidently to real-world computer vision problems and will be able to develop robust and accurate machine-learning models for diverse applications. Whether you are new to machine learning or seeking to enhance your computer vision skills, This book is an invaluable resource for mastering the integration of machine learning and computer vision using OpenCV and Python.
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RecordInfo BibRecord:
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      – Code: 006.37
        Scheme: ddc
        Type: prePub
    Languages:
      – Code: eng
        Text: English
    Subjects:
      – SubjectFull: Computers
        Type: general
      – SubjectFull: Computer vision
        Type: general
      – SubjectFull: Artificial intelligence
        Type: general
      – SubjectFull: Neural networks (Computer science)
        Type: general
      – SubjectFull: Electronic books
        Type: general
      – SubjectFull: Pattern recognition systems
        Type: general
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      – TitleFull: Hands-on ML Projects with OpenCV
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            NameFull: Mugesh S.
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          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2023
            – D: 30
              M: 07
              Type: profile
              Y: 2025
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