🔥 PyTorch Tutorial Series
Is series me hum PyTorch ko step-by-step seekhenge, jisse aap tezi se deep learning models banana shuru kar sakte hain.
Part 1 - What is PyTorch?
PyTorch ka introduction, yeh kyun popular hai, aur iske core features kya hain. Hum basic setup bhi dekhenge.
📘 Start Part 1 →Part 2 - Understanding Tensors
Tensors PyTorch ka fundamental building block hain. Hum seekhenge tensors kaise banayein, manipulate karein, aur unpar operations perform karein.
📘 Start Part 2 →Part 3 - Models as Computation Graphs
Samjhein ki PyTorch me models dynamic computation graphs kaise hote hain aur Autograd (automatic differentiation) kaise kaam karta hai.
📘 Start Part 3 →Part 4 - Automatic Differentiation Made Easy
Learn how PyTorch simplifies automatic differentiation, a crucial aspect of training neural networks.
📘 Start Part 4 →Part 5 - Implementing Multilayer Neural Networks
Dive into implementing multilayer neural networks using PyTorch, understanding the architecture and forward pass.
📘 Start Part 5 →Part 6 - Setting Up Efficient Data Loaders
Discover how to set up efficient data loaders in PyTorch, optimizing data input for training.
📘 Start Part 6 →Part 7 - A Typical Training Loop
Understand and implement a typical training loop in PyTorch, covering forward pass, loss calculation, and backpropagation.
📘 Start Part 7 →Part 8 - Saving and Loading Models
Learn how to save and load trained models in PyTorch, allowing you to reuse and share your models.
📘 Start Part 8 →Part 9 - Optimizing training performance with GPUs
Apne PyTorch training ko GPUs ka use karke kaise speed up karein. Hum CUDA setup aur best practices dekhenge.
📘 Start Part 9 →