How to Learn Object Detection Free Online
Download Applied Computer Vision course free and explore deep learning for image classification, object detection, and recognition using PyTorch.
Applied Computer Vision: Object Detection and Recognition Overview:
This premium video course offers a complete and free learning experience in applied computer vision, focusing on object detection and recognition. You will explore core concepts like image classification, object detection, and both semantic and instance segmentation. The course guides you through real-world datasets such as COCO-2017 and CamVid while using PyTorch and FiftyOne for hands-on implementation. From understanding basic CNNs to training complex models like YOLOv8 and Mask-RCNN, each module enhances your practical understanding of computer vision.
You will start with a strong foundation in convolutional neural networks and gradually progress to advanced topics. This free premium video course builds your confidence in using PyTorch, handling datasets, and evaluating model performance effectively. You will learn by doing, which ensures that you develop skills that apply to real-world computer vision problems. By the end, you will have mastered techniques used in professional image recognition systems.
This course teaches computer vision skills through hands-on PyTorch training using real datasets.
What You’ll Learn in Applied Computer Vision: Object Detection and Recognition:
- Understand image classification, object detection, and segmentation
- Learn how to build and train CNNs using PyTorch
- Apply models like ResNet, YOLOv8, and Faster-RCNN
- Gain experience with semantic and instance segmentation
- Use real-world datasets such as COCO-2017 and CamVid
Course Highlights:
- Comprehensive Curriculum: Covers fundamentals to advanced image recognition models
- Hands-on Learning: Projects and practical exercises using PyTorch and FiftyOne
- Real Datasets: Includes COCO-2017 and CamVid for model training and evaluation
- Advanced Techniques: Learn YOLOv8, Mask-RCNN, and other cutting-edge models
- Focused on Applications: Tailored for aspiring data scientists and AI enthusiasts
Applied CV Course Info:
This video course provides a deep dive into computer vision techniques used in modern AI applications. You will begin with the basics of convolutional neural networks and expand your skills by building classifiers with ResNet and implementing detectors like YOLOv8 and Faster-RCNN. The course leverages Python and PyTorch and includes tools like FiftyOne for visualization and debugging. With practical examples and datasets, learners gain experience with semantic and instance segmentation while mastering end-to-end workflows in image recognition.
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