/londonhack_pytorch

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Londonhack 2019 - Pytorch Tutorial

Tutorial Notebooks for the Pytorch Tutorial at the London Hack 2019

Disclaimer

This material is not intended to be a full course on machine, deep learning, or neural networks, and is meant to introduce basic Pytorch functionality based on a number of examples. Pre-requisites are:

  • Basic Linear Algebra
  • Experience with Python Programming and the scientific python stack (Numpy, Matplotlib, ...) is recommended.
  • Some familiarity with Neural Networks, Optimization, Convolutional Neural Networks and their concepts.

All code is meant to be run on Google Colab and was built on Pytorch 1.0.

Course Material

Session Exercise (Colab) Solutions (Colab)
Getting Started: Google Colab and Logistics Exercise Open In Colab
Session 1: Pytorch, Automatic Differentiation, Neural Nets Exercise Open In Colab Solutions Open In Colab
Session 2: Training Deep Neural Networks Exercise Open In Colab Solutions Open In Colab
Session 3: Convolutional Neural Networks Exercise Open In Colab Solutions Open In Colab
Project: The Seismic-NIST Dataset Dataset Benchmark