Computer Vision with Deep Learning, OpenCV, YOLO, ResNet50

 Buy Now
  

Price: 129.99$

Welcome to the most comprehensive course on Deep Learning concepts. This course empowers you to develop expertise in Computer Vision and Deep Learning foundational concepts, Object Detection, Image Classification and Object Tracking and develop an industry portfolio with the leading-edge in the Machine Learning through this course. In the recent times, innovations of Machine Learning technology have brought in huge technological transformation and most of the business are now shifting towards technology-enabled business models fueled by Deep Learning and Computer Vision. To maintain competitiveness in the industry, it is very important to stay up to date and build expertise on these skills and to fulfill that demand, we have designed this course. This course explains deep learning and computer vision concepts in depth by first explaining the technology concepts and then their implementation through code. Detailed code walkthrough has been included for all the code implementations in projects and source code is available for download. In addition to this, the quiz in the course helps you to assess your knowledge and identify the improvement areas. This course stands apart in its league of courses because of: Detailed Code Walkthrough for all the 6 projects All projects are in working condition and support is provided within 24 hours for any issues faced Selective choice of projects that are in huge demand in industry Comprehensive Coverage of 10 Object Detection models Clear Explanation of 7 Image Classification Models Imparting knowledge on 3 Object Tracking Models Enroll in this course and become specialized in machine learning. Here are just few of the key topics we will be learning and projects that we will design in the course: Neural Network, ANN, CNN along with Activation Function Object Detection Models (Part 1 ) – RCNN, Fast R-CNN, Faster R-CNN, R-FCN Object Detection Models (Part 2 ) – Retina Net, SSD Object Detection Models (Part 3 ) – YOLO, YOLOV3, YOLOV3 Tiny, YOLOV4Image Classification Models (Part 1) – SVM, Decision Tree Image Classification Models (Part 2) – KNN, VGG16, Res Net50, Inception V3, Efficient Net Object Tracking Models – SOT, MOT, Meanshift, SORT, Deep SORT Object Detection using Faster R-CNN Solution License Number Plate Recognition using YOLOV3 Solution YOLOV3 Training for License Number Plate Traffic Sign Detection and Training using SVM Solution Tracking Football Players using Object Tracking Solution