PyTorch Basics and Gradient Descent | Deep Learning with PyTorch: Zero to GANs | Part 1 of 6

“Deep Learning with PyTorch: Zero to GANs” is a beginner-friendly online course offering a practical and coding-focused introduction to deep learning using the PyTorch framework. Learn more and register for a certificate of accomplishment here: http://zerotogans.com/ Watch the entire series here: https://www.youtube.com/playlist?list=PLWKjhJtqVAbm5dir5TLEy2aZQMG7cHEZp Code and Resources: PyTorch basics: https://jovian.ai/aakashns/01-pytorch-basics Linear regression: https://jovian.ai/aakashns/02-linear-regression Machine learning: https://jovian.ai/aakashns/machine-learning-intro Discussion forum: https://jovian.ai/forum/c/pytorch-zero-to-gans/lecture-1-pytorch-basics-linear-regression/63 Topics covered in this video: Introduction to machine learning and Jupyter notebooks PyTorch basics: tensors, gradients, and autograd Linear regression & gradient descent from scratch Using PyTorch modules: nn.Linear & nn.functional This course is taught by Aakash N S, co-founder & CEO of Jovian - a data science platform and global community. - YouTube: https://youtube.com/jovianml - Twitter: https://twitter.com/jovianml - LinkedIn: https://linkedin.com/company/jovianml -- Learn to code for free and get a developer job: https://www.freecodecamp.org Read hundreds of articles on programming: https://freecodecamp.org/news