Top Down Introduction to BERT with HuggingFace and PyTorch
I will also provide some intuition into how BERT works with a top down approach (applications to algorithm).
The Future of (Transfer Learning in) Natural Language Processing
Transfer Learning in Natural Language Processing (NLP): Open questions, current trends, limits, and future directions.
The Illustrated Self-Supervised Learning
A visual introduction to self-supervised learning methods in Computer Vision
Neural Networks for NLP (CMU CS 11-747)
This class will start with a brief overview of neural networks, then spend the majority of the class demonstrating how to apply neural networks to ...
Getting started with JAX (MLPs, CNNs & RNNs)
Learn the building blocks of JAX and use them to build some standard Deep Learning architectures (MLP, CNN, RNN, etc.).
How to Train Your Neural Net
Deep learning for various tasks in the domains of Computer Vision, Natural Language Processing, Time Series Forecasting using PyTorch 1.0+.
NLP Model Selection
NLP model selection guide to make it easier to select models. This is prescriptive in nature and has to be used with caution.
A Visual Guide to Recurrent Layers in Keras
Understand how to use Recurrent Layers like RNN, GRU and LSTM in Keras with diagrams.
Deep Tutorials for PyTorch
This is a series of in-depth tutorials I'm writing for implementing cool deep learning models on your own with the amazing PyTorch library.
Reproduces the book Dive Into Deep Learning (www.d2l.ai), adapting the code from MXNet into PyTorch.
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Share a project
Share something interesting you found that's made with ML.
Share what you've made with ML.