Modern Computer Vision with PyTorch
A practical roadmap from deep learning fundamentals to advanced applications and Generative AI
VACreated by Yeshwanth Reddy, V Kishore Ayyadevara
Explore practical computer vision techniques using PyTorch and deep learning. Build and optimize neural networks, tackle real-world image tasks, and experiment with the latest generative AI models. Move from foundational concepts to advanced applications, including deploying models in production environments.
Packt | Jun 2024 | 746 min
What You Will Learn
You will work through hands-on projects that cover a range of computer vision problems, from basic image classification to advanced generative models. Each project builds on the last, helping you develop practical skills and confidence. By experimenting with real datasets and modern tools, you will gain experience that translates directly to real-world scenarios.
Key Features
- Master neural network architectures for image classification, detection, and segmentation
- Apply transformer-based and generative models to solve real-world vision challenges
- Learn to deploy computer vision models efficiently using best practices
Target Audience
Designed for those with basic Python and machine learning knowledge, this course is ideal for intermediate learners and early-career practitioners in computer vision. If you want to deepen your understanding of deep learning and PyTorch while solving practical vision problems, you will find clear guidance and actionable projects to help you reach your goals.
