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Module · 6 lessons

Deep Learning with PyTorch

Build, train, and regularize deep networks using PyTorch tensors, autograd, and nn.Module.

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At a glance

Level
Advanced
Lessons
6 lessons
Time to complete
2–3 weeks
Cost
Free forever · no sign-up

PyTorch is one of the two leading deep learning frameworks. This module teaches you to work with tensors and automatic differentiation, build networks with nn.Sequential, write training loops, and regularize deep models — finishing with a real prediction project.

Lessons in this module

1 Deep Learning Fundamentals Understand what deep learning is, where it beats classical machine learning, and why frameworks like PyTorch make neural networks practical 2 Tensors and Autograd in PyTorch Learn PyTorch tensors and autograd by working with the real Indian IPO dataset, from creating tensors to computing gradients automatically 3 Building Neural Networks with nn.Sequential Define neural networks in PyTorch with nn.Module, nn.Linear, and nn.Sequential by building a real IPO classifier 4 Training Neural Networks Master the full PyTorch training loop and train a real binary classifier on the Indian IPO dataset 5 Deep Networks and Regularization Go deeper with PyTorch and fight overfitting using dropout and weight decay on the real Indian IPO dataset 6 Guided Project: Predicting IPO Listing Gains with PyTorch Assemble everything you have learned into one end-to-end PyTorch project that predicts IPO listing gains on the real Indian IPO dataset
Achievement

Complete all 6 lessons to finish the Deep Learning with PyTorch module.

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