Master Computer Vision & Deep Learning: OpenCV, YOLO, ResNet

Master Computer Vision & Deep Learning: OpenCV, YOLO, ResNet, available at $54.99, has an average rating of 4.75, with 76 lectures, 3 quizzes, based on 32 reviews, and has 125 subscribers.

You will learn about Master the fundamentals of deep learning, including neurons, neural networks, and activation functions Discover the architecture and design of state-of-the-art object detection models, such as Faster R-CNN, RetinaNet, SDD, and YOLO Build a real-world object detection application to automatically detect license plate numbers using Faster R-CNN Learn about the architecture and design of image classification models, such as SVM, VGG-16, ResNet50, and InceptionV3 Develop an image classification application to detect and train traffic sign boards using SVM Train an image classification model using ResNet to classify 20 different sets of multiple images Understand the design of object tracking frameworks, such as Meanshift, SORT, and DeepSORT Build a solution to track football players using object tracking This course is ideal for individuals who are Software engineers who want to learn deep learning and computer vision to develop cutting-edge machine learning solutions. or Machine learning enthusiasts who want to develop a portfolio of industry-relevant projects or Data scientists who want to expand their skills and knowledge in deep learning and computer vision or Students who want to gain hands-on experience with deep learning and computer vision or Professionals who want to transition into a career in machine learning It is particularly useful for Software engineers who want to learn deep learning and computer vision to develop cutting-edge machine learning solutions. or Machine learning enthusiasts who want to develop a portfolio of industry-relevant projects or Data scientists who want to expand their skills and knowledge in deep learning and computer vision or Students who want to gain hands-on experience with deep learning and computer vision or Professionals who want to transition into a career in machine learning.

Enroll now: Master Computer Vision & Deep Learning: OpenCV, YOLO, ResNet

Summary

Title: Master Computer Vision & Deep Learning: OpenCV, YOLO, ResNet

Price: $54.99

Average Rating: 4.75

Number of Lectures: 76

Number of Quizzes: 3

Number of Published Lectures: 76

Number of Published Quizzes: 3

Number of Curriculum Items: 79

Number of Published Curriculum Objects: 79

Original Price: $119.99

Quality Status: approved

Status: Live

What You Will Learn

• Master the fundamentals of deep learning, including neurons, neural networks, and activation functions
• Discover the architecture and design of state-of-the-art object detection models, such as Faster R-CNN, RetinaNet, SDD, and YOLO
• Build a real-world object detection application to automatically detect license plate numbers using Faster R-CNN
• Learn about the architecture and design of image classification models, such as SVM, VGG-16, ResNet50, and InceptionV3
• Develop an image classification application to detect and train traffic sign boards using SVM
• Train an image classification model using ResNet to classify 20 different sets of multiple images
• Understand the design of object tracking frameworks, such as Meanshift, SORT, and DeepSORT
• Build a solution to track football players using object tracking

Who Should Attend

• Software engineers who want to learn deep learning and computer vision to develop cutting-edge machine learning solutions.
• Machine learning enthusiasts who want to develop a portfolio of industry-relevant projects
• Data scientists who want to expand their skills and knowledge in deep learning and computer vision
• Students who want to gain hands-on experience with deep learning and computer vision
• Professionals who want to transition into a career in machine learning

Target Audiences

• Software engineers who want to learn deep learning and computer vision to develop cutting-edge machine learning solutions.
• Machine learning enthusiasts who want to develop a portfolio of industry-relevant projects
• Data scientists who want to expand their skills and knowledge in deep learning and computer vision
• Students who want to gain hands-on experience with deep learning and computer vision
• Professionals who want to transition into a career in machine learning