Training Deep Neural Networks on a GPU | Deep Learning with PyTorch: Zero to GANs | Part 3 of 6

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United States freeCodeCamp.org
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Published on ● Video Link: https://www.youtube.com/watch?v=Qn5DDQn0fx0


Duration: 1:50:30
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“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:
Feedforward neural networks: https://jovian.ai/aakashns/04-feedforward-nn
Neural networks (minimal): https://jovian.ai/aakashns/fashion-feedforward-minimal
Data Visualization Cheatsheet: https://jovian.ai/aakashns/dataviz-cheatsheet
Discussion forum: https://jovian.ai/forum/t/lecture-3-training-deep-neural-networks-on-a-gpu/13762

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

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

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