Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
3 Hour(s) 50 Minute(s)
Language
English
Taught by
Vineeta Vashistha
Rating
4 views
Course Overview
Unlock the Power of Object Detection with Deep Learning: YOLO, SSD, SVM, ResNet50, Inceptionv3 and CNNs
Master Deep Learning and Computer Vision: From Foundations to Cutting-Edge Techniques
Elevate your career with a comprehensive deep dive into the world of machine learning, with a focus on object detection, image classification, and object tracking.
This course is designed to equip you with the practical skills and theoretical knowledge needed to excel in the field of computer vision and deep learning. You'll learn to leverage state-of-the-art techniques, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and advanced object detection models like YOLOv8.
Key Learning Outcomes:
Fundamental Concepts:
Grasp the core concepts of machine learning and deep learning, including supervised and unsupervised learning.
Understand the mathematical foundations of neural networks, such as linear algebra, calculus, and probability theory.
Computer Vision Techniques:
Master image processing techniques, including filtering, noise reduction, and feature extraction.
Learn to implement various object detection models, such as YOLOv8, Faster R-CNN, and SSD.
Explore image classification techniques, including CNN architectures like ResNet, Inception, and EfficientNet.
Dive into object tracking algorithms, such as SORT, DeepSORT, and Kalman filtering.
Practical Projects:
Build real-world applications, such as license plate recognition, traffic sign detection, and sports analytics.
Gain hands-on experience with popular deep learning frameworks like TensorFlow and PyTorch.
Learn to fine-tune pre-trained models and train custom models for specific tasks.
Why Choose This Course?
Expert Instruction: Learn from experienced instructors with a deep understanding of deep learning and computer vision.
Hands-On Projects: Gain practical experience through a variety of real-world projects.
Comprehensive Curriculum: Cover a wide range of topics, from foundational concepts to advanced techniques.
Flexible Learning: Access course materials and assignments at your own pace.
24/7 Support: Get timely assistance from our dedicated support team.
Join us and unlock the power of deep learning to shape the future of technology.
Course Content
- 10 section(s)
- 79 lecture(s)
- Section 1 Course Starter
- Section 2 Understanding Computer Vision and AI
- Section 3 Tools Setup
- Section 4 Neuron, Neural Network and Activation Function
- Section 5 Object Detection - R-CNN, FAST R-CNN, RPN, FASTER R-CNN and R-FCN
- Section 6 Project 1 - Object Detection using Faster R-CNN
- Section 7 Object Detection - RetinaNet, SSD, YOLO, YOLOV3, YOLOV3 Tiny and YOLOV4
- Section 8 Project 2 - License Number Plate Recognition using YOLOV3
- Section 9 Image Classification Models - SVM, Decision Tree, KNN
- Section 10 Project 3 - YOLOV3 Training for License Number Plate
What You’ll 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
Skills covered in this course
Reviews
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SSaksham Dutt
I want to extend my heartfelt appreciation for the transformative journey I've had through your Deep Learning and Computer Vision course. It's been an enriching experience filled with hands-on learning and practical insights. Your course stands out for its: a) Practical Mastery: The emphasis on code walkthroughs ensured not just understanding but mastery of concepts. b) Relevance: Industry-ready projects and round-the-clock support made learning seamless and applicable. c) Comprehensive Coverage: Exploring various models equipped me with a diverse skill set ready for real-world challenges. d) Real-World Applications: The opportunity to apply knowledge to projects like License Number Plate Recognition was invaluable. Thank you for empowering me with the skills and confidence to excel in Machine Learning and Computer Vision.
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SShriya
The course's comprehensive coverage of Object Detection, Image Classification, and Object Tracking Models provided a strong foundation for me. The code walkthroughs and the selection of projects tailored to job market demand were fantastic. The real-world applications, especially License Number Plate Recognition and Traffic Sign Detection, were insightful. Sports Analytics was a unique and engaging addition. This course has empowered me with the skills and knowledge to confidently embrace a career in machine learning and computer vision. I highly recommend it to anyone seeking deep learning mastery.
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PPrateek Grag
Only course that explains the model so well along with their implementation for practical usage. Strongly recommend this course
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EEric
This course is a great start for anyone who ants to learn Deep Learning. I really like the diversity of projects in the course and their detailed explanation in code walkthrough
