Mastering Computer Vision with TensorFlow 2.x: Build advanced computer vision applications using machine learning and deep learning techniques
By the end of this book, you'll have a solid understanding of computer vision and be able to confidently develop models to automate tasks.
Mastering Computer Vision with TensorFlow 2.x: Build advanced computer vision applications using machine learning and deep learning techniques
Numéro d'article: 45913771

Mastering Computer Vision with TensorFlow 2.x: Build advanced computer vision applications using machine learning and deep learning techniques

Numéro d'article: 45913771

XOF 46038

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By the end of this book, you'll have a solid understanding of computer vision and be able to confidently develop models to automate tasks.
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Ce qui se démarque

Comprehensive Guide
Offers in-depth explanations and tutorials on computer vision applications, making complex concepts accessible for beginners and advanced learners alike.
Hands-On Projects
Includes real-world projects that enhance practical skills, allowing users to apply machine learning and deep learning techniques effectively in various scenarios.
Updated Framework
Focuses on TensorFlow 2.x, ensuring users learn the latest tools and practices in machine learning, aligning with industry standards for advanced computer vision solutions.

Détails du produit

Build advanced computer vision applications with TensorFlow 2.x. Learn machine learning and deep learning techniques. Shop now at Ubuy, a Burkina Faso.
Publisher Packt Publishing
Publication date May 15, 2020
Language English
Print length 430 pages
ISBN-10 1838827064
ISBN-13 978-1838827069
Item Weight 1.62 pounds (730 grams)
Dimensions 7.5 x 0.97 x 9.25 inches (19.1 x 2.5 x 23.5 cm)

À qui est-ce destiné ?

Suitable For
  • Aspiring Data Scientists

    Individuals looking to enhance their skills in machine learning specifically focused on computer vision applications.

  • Developers in AI

    Software engineers interested in incorporating advanced computer vision functionalities into their applications using TensorFlow.

  • Research Academics

    Academics and researchers seeking to apply deep learning techniques in computer vision for innovative projects and studies.

Not Suitable For
  • Complete Beginners

    Users without a background in programming or machine learning might find the content difficult to understand.

DESCRIPTION DU PRODUIT

Mastering Computer Vision with TensorFlow 2.x: Build advanced computer vision applications using machine learning and deep learning techniques

Vous avez une question ? Chattez avec nous

Questions et réponses des clients

  • question: Do I need prior experience with TensorFlow?

    répondre: Yes, familiarity with TensorFlow is required to get started with this book.
  • question: Is this book suitable for beginners in computer vision?

    répondre: This book is designed for individuals with some knowledge of machine learning and deep learning.
  • question: What key topics are covered in this book?

    répondre: Key topics include image processing, object detection, neural network architectures, and model optimization.

Computer Vision & Pattern Recognition Editorial Review

In this editorial review, the featured book on computer vision comes highly recommended for both newcomers and those with some background in machine learning concepts. Many users found it to be an excellent starting point, blending theoretical knowledge with practical applications through well-written explanations and functional code snippets. The distinct advantage of having a GitHub repository linked to the book stands out, allowing readers to easily replicate code and engage with the material effectively—many reviewed the implementation as seamless and enjoyable. The book covers a variety of topics, including object detection and classification, while also providing insights into model deployment on mobile devices—a feature that users commend for its practicality. Despite these strengths, some critiques mention that the focus leans heavily towards image-based applications, with fewer examples and discussions around video inputs. Additionally, a desire for deeper intuitive insights alongside the mathematical explanations indicates room for enhancement in content delivery. Overall, readers appreciate the author's responsiveness and support, enhancing the learning experience. The reviews reflect a clear Consensus on the book being a valuable resource in the computer vision field, leaving users eager for more advanced material that could delve deeper into TensorFlow and IoT applications. **

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Avantages

  • Strong balance between theory and practical code snippets
  • GitHub repository for easy code replication
  • Comprehensive coverage of object detection, classification, and deployment
  • Author provides helpful support through LinkedIn

Les inconvénients

  • Focus primarily on image applications, with less on video applications

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