MLH Show & Tell: Introduction to PyTorch

Video • Jupyter Notebook • Supplementary Materials

The repository contains all the resources for the MLH Pod 2.1.0's show & Tell. The Show & Tell will give a brief introduction to pytorch. Topics discussed are tensors, computational graphs, autograd. Finally, building a linear model and simple neural network to get an understanding of the workflow in PyTorch.

Topics Covered

1. Tensors
2. Computational Graphs - Autograd
3. Datasets & Dataloaders
4. Linear Regression
5. Simple Neural Network

How to Get Started (Supplementary Materials)

Courses

1. Top-down Approach (Application →Foundational Concepts)
   • Practical Deep Learning Course - https://course.fast.ai/
2. Bottom-Up Approach (Foundational Concepts → Application)

   • Deep Learning from the Foundations - https://course19.fast.ai/part2

   • Machine Learning (Stanford) - https://www.coursera.org/learn/machine-learning

   • CS231n - Convolutional Neural Networks for Visual Recognition (Andrej Karpathy)

     https://www.youtube.com/watch?v=NfnWJUyUJYU&list=PLkt2uSq6rBVctENoVBg1TpCC7OQi31AlC

   • Deep Learning Specialization

     https://www.coursera.org/specializations/deep-learning

   • Natural Language Processing

     https://www.coursera.org/specializations/natural-language-processing

• Full stack Deep Learning - https://fall2019.fullstackdeeplearning.com/

Books

1. Neural Networks and Deep Learning

   http://neuralnetworksanddeeplearning.com/index.html

2. Course in Machine Learning

   http://ciml.info/

3. Deep Learning (Ian Goodfellow)

   https://www.deeplearningbook.org/

Special Mentions

1. http://jalammar.github.io/ (The BEST blog posts about transformers and BERT)