Item #:
142556317
Hands-on ML Projects with OpenCV: Master computer vision and Machine Learning using OpenCV and Python (English Edition) (Machine Learning Engineer
85% of respondents would recommend this to a friend
Item #:
142556317
QAR 219
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Master computer vision and Machine Learning using OpenCV and Python, empowering you to tackle complex tasks confidently.
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What Stands Out
Hands-On Approach
Engages learners through practical, real-world projects, ensuring a strong grasp of computer vision and machine learning concepts with OpenCV and Python.
Large Print Format
Designed for easy reading, the large print format caters to a broader audience, including those with visual impairments, enhancing overall accessibility.
Updated Content
Released in August 2023, this edition covers the latest advancements in OpenCV, ensuring readers are equipped with contemporary skills essential for today's tech landscape.
Product Details
- Be at your A game in building Intelligent systems by leveraging Computer vision and Machine Learning.Key Features● Step-by-step instructions and code snippets for real world ML projects.● Covers entire spectrum from basics to advanced concepts such as deep learning, transfer learning, and model optimization● Loaded with practical tips and best practices for implementing machine learning with OpenCV for optimising your workflow.Book DescriptionThis 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.What you will learn● Learn how to work with images and perform basic image processing tasks using OpenCV.● Implement machine learning techniques to computer vision tasks such as image classification, object detection, and image segmentation.● Work on real-world projects and datasets to gain hands-on experience in applying machine learning techniques with OpenCV.● Explore the concepts of deep learning using Tensorflow and Keras and how it can be used for computer vision tasks.● Understand the concept of transfer learning and how pre-trained models can be leveraged for new tasks.● Utilize techniques for model optimization and deployment in resource-constrained environments.Who is this book for?This book is for everyone with a basic understanding of programming and who wants to apply machine learning in computer vision using OpenCV and Python. Whether you're a student, researcher, or developer, this book will equip you with practical skills for machine learning projects. Some familiarity with Python and machine learning concepts is assumed.Table of ContentsChapter 1: Getting Started With OpenCVChapter 2: Basic Image & Video Analytics in OpenCVChapter 3: Image Processing 1 using OpenCVChapter 4: Image Processing 2 using OpenCVChapter 5: Thresholding and Contour Techniques Using OpenCVChapter 6: Detect Corners and Road Lane using OpenCVChapter 7: Object And Motion Detection Using OpencvChapter 8: Image Segmentation and Detecting Faces Using OpenCVChapter 9: Introduction to Deep Learning with OpenCVChapter 10: Advance Deep Learning Projects with OpenCVChapter 11: Deployment of OpenCV projectsAbout the AuthorMugesh S. works as a Data Scientist at Infosys, with a passion for leveraging data-driven insights to tackle complex challenges and drive business success. He is an engineering graduate who completed the PG program in Data Science and Engineering, as well as a Master’s in Mathematics and Data Science, to deepen his understanding of the intricacies of data analytics.
| Publisher | Orange Education Pvt Ltd |
| Publication date | 9 Aug. 2023 |
| Language | English |
| Print length | 336 pages |
| ISBN-10 | 9388590872 |
| ISBN-13 | 978-9388590877 |
| Dimensions | 19.05 x 1.93 x 23.5 cm |
| Book 1 of 1 | Machine Learning Engineer (OpenCV) — Focused Path |
Who Should Buy?
-
Aspiring Developers
Ideal for beginners looking to learn computer vision through hands-on projects using Python and OpenCV.
-
Educators and Trainers
Great resource for professionals creating courses or training sessions focused on machine learning and computer vision.
-
Hobbyists and Enthusiasts
Perfect for tech enthusiasts wanting to experiment with computer vision projects and broaden their programming skills.
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Advanced Practitioners
Experienced practitioners may find the content too basic and lacking in advanced techniques or in-depth analysis.
Product Description
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English edition Mugesh S. , Orange AVA Format: Paperback Editorial Review
Hands-on ML Projects With OpenCV: Master Computer Vision And Machine Learning Using OpenCV And Python (English Edition) offers an in-depth exploration into the world of computer vision and machine learning through practical projects. Published on 9 Aug. 2023 by Orange Education Pvt Ltd, this English-language book spans 336 pages and is tailored for aspiring machine learning engineers focusing on OpenCV applications. Readers will appreciate its structured approach to learning, which emphasizes hands-on projects ensuring that theoretical concepts are backed by practical experience. This resource serves as a great introduction to mastering essential skills in AI and CV.
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Pros
- Comprehensive coverage of computer vision concepts
- Hands-on projects enhance learning experience
- Suitable for both beginners and experienced users
- Well-structured content for easy understanding
- Latest publication with updated practices
Cons
- Some prior knowledge of machine learning may be helpful
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Features & Benefits
- Step-by-step instructions for real-world ML projects.
- Covers basic to advanced concepts including deep learning and model optimization.
- Hands-on projects with real-world datasets for practical experience.
- Practical tips and best practices to optimize workflow.
- Suitable for beginners to advanced users in programming and ML.
- Master integration of ML with computer vision using OpenCV.
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