PyTorch in Practice: An Applications-First Approach (LFD473)
This four-day course introduces you to the PyTorch framework and gets you going with developing applications that incorporate AI via PyTorch using both lectures and hands-on assignments. The course concentrates specifically on pretrained models for Computer Vision and Natural Language Processing tasks from the PyTorch and HuggingFace ecosystems.
Suggested prerequisites: None. Python experience may be of advantage.
Audience: Machine Learning practitioners with interest in Deep Learning with PyTorch
This course is tailored for machine learning practitioners eager to dive into deep learning using PyTorch. It focuses on practical applications, allowing you to prototype AI solutions that address real-world challenges in areas like computer vision and natural language processing.
Throughout the course, you will gain hands-on experience with powerful pretrained models, enabling you to quickly develop and deploy applications. You’ll learn how to fine-tune these models using your own data, which means you can create customized solutions that meet your specific needs. The course is designed to be interactive, with practical lab exercises that reinforce your learning and help you apply new concepts immediately.
You will have direct access to experienced instructors who will guide you through each step of the process, ensuring you feel supported as you learn. By the end of the course, you will not only have a solid understanding of how to use PyTorch effectively but also the confidence to tackle complex AI projects.