If you’re looking for a comprehensive course that covers machine learning on videos through video analytics, object detection, and image classification, then the "Object Detection on Videos - Deep Learning" course is for you!
Course Overview
The course content covers everything you need to know about implementing video analytics using a three-step process of capturing, processing, and saving video. Also, you will gain an understanding of the various object detection models and how to implement them for a real-time case study using social distancing as a practical example. Furthermore, learn how to create a model on face mask detection using image classification models, transfer learning, and leverage your skills to implement a solution of face mask detection in an algorithmic and machine learning approach.
Course Rating and Reviews
With 66 reviews and the average course rating of 4.29992, it is evident that this course is of great value to learners. And this isn't surprising, given the course's well-structured content, hands-on tutorials, and comprehensive coverage of object detection and image classification models.
Course Headline
The course’s headline, "Quick Starter on Object Detection and Image Classification on Videos using Deep Learning, OpenCV, YOLO and CNN Models," is an apt description of what you'll be learning. The course structure has been expertly crafted to provide learners with hands-on tutorials with various models such as OpenCV, YOLO, HOG Faster RCNN, and others.
Course Description
The course’s description provides an overview of the coverage of the course content. Expect a step-by-step process of creating an object detection solution on videos using machine learning models. In addition, you'll learn about the various object detection models such as Haar Cascade, HOG, Faster RCNN, R-FCN, SSD, YOLO, and much more. Also, the course provides source code and tutorials on people footfall tracking and automatic parking management projects.
This course is ideal for machine learning developers and enthusiasts who want to enhance their skills in video analytics, object detection, and machine learning algorithms.
Course Curriculum
The course curriculum is designed to provide an in-depth understanding of various video analytics, video processing, object detection, and image classification models:
Video Analytics Architecture
The course begins by introducing you to video analytics architecture. In this section, you will learn the basics of video analysis and how it is used in real-world applications.
Euclidean Distance
The next topic is the Euclidean Distance and how it is used to calculate distance between two points. You’ll gain insights into how it is used in object detection and tracking.
Object Detection Models - Haar Cascade, HOG, Faster RCNN, R-FCN, SSD, YOLO
This topic focuses on various object detection models such as Haar Cascade, HOG, Faster RCNN, R-FCN, SSD, and YOLO. You will gain an understanding of how each method works and when to use them.
Object Detection Model Implementation on Videos with Haar Cascade, HOG and YOLO
The course then moves to the implementation of object detection models on videos using Haar Cascade, HOG and YOLO models. You get to see how each works in action.
Image Classification
This section focuses on image classification, a pre-training method in machine learning model. You will learn how to classify images into categories.
Training Image Classification Model on Google Colab
You will be introduced to Google Colab and how it is used in training image classification models. This section provides a hands-on tutorial on how to use Google Colab.
Image Classification Implementation on Videos with Trained InceptionV3 Model
This section brings everything together, showing you how to utilize your newly learned skills. You will be introduced to image classification implementation on videos with a trained InceptionV3 model.
Object Tracking with SORT Framework
Here you will learn how to track objects, including humans, using the simple online and real-time tracking (SORT) framework.
People Footfall Tracking Solution
You will get to see people footfall tracking in action with practical use cases.
Automatic Parking Management Solution
The course will wrap up by showcasing automatic parking management solutions with a demo providing real-world applications of the knowledge gained.
Reasons to Take This Course
The "Object Detection on Videos - Deep Learning" course is a must-have for anyone seeking to enhance their skills in object detection using various models and machine learning techniques. The following are some reasons to take this course:
- Dedicated in-course support is provided within 24 hours for any issues faced
- Line-by-line code walkthrough of object detection implementation on videos and training a model for image classification
- Comprehensive coverage of object detection and image classification models
- Working source code for people footfall tracking and automatic parking management project
Takeaway
The "Object Detection on Videos - Deep Learning" course provides comprehensive coverage of various object detection and image classification models, including real-world applications such as people footfall tracking and automatic parking management solutions. With dedicated in-course support and line-by-line code walkthroughs, this course is ideal for machine learning developers and enthusiasts seeking to enhance their skills in video analytics and object detection.
