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.
Data analysis made easy: Text2Code for Jupyter notebook
A jupyter notebook extension for Text2Code for basic pandas and plotly commands
Image segmentation in 2020
Architectures, Losses, Datasets, and Frameworks
Transformers - Hugging Face
🤗 Transformers: State-of-the-art Natural Language Processing for TensorFlow 2.0 and PyTorch.
A Visual Guide to Recurrent Layers in Keras
Understand how to use Recurrent Layers like RNN, GRU and LSTM in Keras with diagrams.
An Illustrated Guide to Graph Neural Networks
A breakdown of the inner workings of GNNs.
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 ...
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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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