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Computer Vision Smart Systems : Python, Yolo And Opencv -1
Published 10/2024
Created by Yılmaz Alaca
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 88 Lectures ( 6h 40m ) | Size: 2.4 GB
[/center]
Develop Your Own Computer Vision Smart System with Python and YOLO | Step-by-Step | OpenCV | Real-Time Object Detection
What you'll learn
Introduction to Image Processing and Computer Vision,
Object Detection with YOLO Algorithm
Building Custom Deep Learning Models
Practical Vehicle Counting Project
Project Development and Implementation
Requirements
No Prior Experience Required
Basic Computer Skills
Eagerness to Learn
Description
This course is designed for anyone interested in pursuing a career in artificial intelligence and computer vision or looking to implement computer vision applications in their projects. In "Computer Vision Smart Systems: Python, YOLO, and OpenCV -1," we start with the fundamentals of computer vision and cover image processing techniques using the Python programming language and OpenCV library. Then, we advance to object detection and deep learning modeling using the YOLO (You Only Look Once) algorithm. Students will learn to build custom deep learning models from scratch, work with datasets, perform object detection, and apply these models in various projects.Throughout the course, practical exercises are provided step-by-step along with theoretical knowledge, giving students the chance to apply what they've learned. Additionally, we address common challenges you may face and provide detailed solutions. Aimed at building skills from basic to intermediate levels, this course serves as a comprehensive guide for anyone interested in the field of computer vision. It empowers you to develop smart systems for your projects and enhances your expertise in this exciting domain."You are never too old to set another goal or to dream a new dream." - C.S.Lewis"Do the difficult things while they are easy and do the great things while they are small. A journey of a thousand miles begins with a single step" - Lao TzuYou get the best information that I have compiled over years of trial and error and experience!Best wishes,Yılmaz ALACA
Who this course is for
Beginners in Programming: Individuals with no prior programming experience who want to learn Python and apply it to real-world applications in computer vision.
Aspiring Data Scientists: Those looking to enter the field of data science and machine learning, particularly in the domain of computer vision.
Students and Professionals: College students, recent graduates, or professionals seeking to expand their skill set in artificial intelligence and image processing.
Hobbyists and Enthusiasts: Anyone with a keen interest in technology, artificial intelligence, or robotics who wants to explore how computer vision systems are built.
Developers Transitioning to AI: Programmers or software developers wanting to branch into the field of artificial intelligence and machine learning, specifically in computer vision.
Project-Based Learners: Individuals who learn best through hands-on projects and practical applications, as this course includes a final project on vehicle counting.
Homepage
Computer Vision Smart Systems : Python, Yolo And Opencv -1
Published 10/2024
Created by Yılmaz Alaca
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 88 Lectures ( 6h 40m ) | Size: 2.4 GB
[/center]
Develop Your Own Computer Vision Smart System with Python and YOLO | Step-by-Step | OpenCV | Real-Time Object Detection
What you'll learn
Introduction to Image Processing and Computer Vision,
Object Detection with YOLO Algorithm
Building Custom Deep Learning Models
Practical Vehicle Counting Project
Project Development and Implementation
Requirements
No Prior Experience Required
Basic Computer Skills
Eagerness to Learn
Description
This course is designed for anyone interested in pursuing a career in artificial intelligence and computer vision or looking to implement computer vision applications in their projects. In "Computer Vision Smart Systems: Python, YOLO, and OpenCV -1," we start with the fundamentals of computer vision and cover image processing techniques using the Python programming language and OpenCV library. Then, we advance to object detection and deep learning modeling using the YOLO (You Only Look Once) algorithm. Students will learn to build custom deep learning models from scratch, work with datasets, perform object detection, and apply these models in various projects.Throughout the course, practical exercises are provided step-by-step along with theoretical knowledge, giving students the chance to apply what they've learned. Additionally, we address common challenges you may face and provide detailed solutions. Aimed at building skills from basic to intermediate levels, this course serves as a comprehensive guide for anyone interested in the field of computer vision. It empowers you to develop smart systems for your projects and enhances your expertise in this exciting domain."You are never too old to set another goal or to dream a new dream." - C.S.Lewis"Do the difficult things while they are easy and do the great things while they are small. A journey of a thousand miles begins with a single step" - Lao TzuYou get the best information that I have compiled over years of trial and error and experience!Best wishes,Yılmaz ALACA
Who this course is for
Beginners in Programming: Individuals with no prior programming experience who want to learn Python and apply it to real-world applications in computer vision.
Aspiring Data Scientists: Those looking to enter the field of data science and machine learning, particularly in the domain of computer vision.
Students and Professionals: College students, recent graduates, or professionals seeking to expand their skill set in artificial intelligence and image processing.
Hobbyists and Enthusiasts: Anyone with a keen interest in technology, artificial intelligence, or robotics who wants to explore how computer vision systems are built.
Developers Transitioning to AI: Programmers or software developers wanting to branch into the field of artificial intelligence and machine learning, specifically in computer vision.
Project-Based Learners: Individuals who learn best through hands-on projects and practical applications, as this course includes a final project on vehicle counting.
Homepage
کد:
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