Courses & Tutorials
Collection of courses
Full Stack Deep Learning
Full Stack Deep Learning helps you bridge the gap from training machine learning models to deploying AI systems in the real world.
MLOps Tutorial Series
How to create an automatic model training & testing setup using GitHub Actions and Continuous Machine Learning (CML).
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 ...
Simple Transformers: Transformers Made Easy
Simple Transformers removes complexity and lets you get down to what matters – model training and experimenting with the Transformer model architectures.
Understanding Generative Adversarial Networks (GANs)
Building, step by step, the reasoning that leads to GANs.
History of Language Models - Alec Radford
A quick history of language models
Computational Linear Algebra for Coders
Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course.
Tensor functions for Pytorch's Autograd
A blog and notebook to understand the Pytorch's autograd.
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