Training Deep Neural Networks on a GPU | Deep Learning with PyTorch (3/6)

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Using GPU to train Deep Neural Networks, Creating a multilayer neural network using nn.Module, Classifying images from the Fashion MNIST Dataset and much more. This lecture is part 3/6 of the Deep Learning with PyTorch Free Certification course. To learn more visit https://jovian.ai/learn/deep-learning...

Time Breaks:
00:00 Introduction
2:54 Training Deep Neural Network on a GPU
15:45 Hidden Layers, Activation Functions and Non-Linearity
35:49 Defining our Model
45:05 Using a GPU
56:59 Training the Model
1:17:59 Classifying Images from Fashion MNIST (Feedforward Networks)
1:27:24 Assignment 3 - Feedforward Neural Networks
1:42:03 Course Overview
1:43:45 What to do next?

Code and Resources:
🔗 Feedforward neural networks: https://jovian.ai/aakashns/04-feedfor...
🔗 Neural networks (minimal): https://jovian.ai/aakashns/fashion-fe...
🔗 Data Visualization Cheatsheet: https://jovian.ai/aakashns/fashion-fe...
🔗 Discussion forum: https://jovian.ai/forum/t/lecture-3-t...

Topics covered in this video:
⌨️ Working with cloud GPU platforms like Kaggle & Colab
⌨️ Creating a multilayer neural network using nn.Module
⌨️ Activation function, non-linearity, and universal approximation theorem
⌨️ Moving datasets and models to the GPU for faster training

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.
You can learn more and register for a Free Certificate of Accomplishment at http://zerotogans.com.

This course is taught by Aakash N S, co-founder & CEO of Jovian - a platform for sharing, showcasing and collaborating on data science projects online.

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