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

“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 -- Learn to code for free and get a developer job: https://www.freecodecamp.org Read hundreds of articles on programming: https://freecodecamp.org/news