Tensorflow, pytorch and other relevant resources for learning computer vision, machine learning & deep learning techniques using code, examples and ...
Machine Learning Basics
A practical set of notebooks on machine learning basics, implemented in both TF2.0 + Keras and PyTorch.
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.
Creating an End-to-End Machine Learning Application
A complete, end-to-end ML application, implemented in both TensorFlow 2.0 and PyTorch.
Building Machine Learning Products: A Problem Well-Defined
In this post, we'll dig deeper into how to develop the requirements for a machine learning project when you're given a vague problem to solve.
A Visual Guide to Recurrent Layers in Keras
Understand how to use Recurrent Layers like RNN, GRU and LSTM in Keras with diagrams.
Image segmentation in 2020
Architectures, Losses, Datasets, and Frameworks
Self-Supervised Scene De-occlusion
We investigate the problem of scene de-occlusion, which aims to recover the underlying occlusion ordering and complete the invisible parts of occluded ...
An Illustrated Guide to Graph Neural Networks
A breakdown of the inner workings of GNNs.
Transformers - Hugging Face
🤗 Transformers: State-of-the-art Natural Language Processing for TensorFlow 2.0 and PyTorch.
Shape inference for PyTorch (like Keras) & new layers
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I'm a multipotentialite who loves to learn new things and work on solving challenges problems. Passionate about AI and Physics. Currently working on AI & CV.
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