This is a beginner-friendly coding-first online course on PyTorch - one of the most widely used and fastest growing frameworks for machine learning. This video covers the basic concepts in PyTorch viz. tensors & gradients, and walks through the process of implementing linear regression and gradient descent - the foundational algorithms in machine learning. Resources: 🔗 PyTorch Basics: https://jovian.ml/aakashns/01-pytorch... 🔗 Linear Regression: https://jovian.ml/aakashns/02-linear-... 🔗 Machine Learning Intro: https://jovian.ml/aakashns/machine-le... 🔗 Discussion forum: https://jovian.ml/forum/t/lecture-1-p... 🔗 Programming Assignment: https://jovian.ml/forum/t/assignment-... Topics covered: ⌨️ Introduction to Machine Learning & Deep Learning ⌨️ PyTorch Basics: Tensors, Gradients & Autograd ⌨️ Linear Regression and gradient descent from scratch using Tensor operations ⌨️ Linear Regression using PyTorch built-ins (nn.Linear, nn.functional etc.)