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🔬 Some personal research code on analyzing CNNs. Started with a thorough exploration of Stanford's Tiny-Imagenet-200 dataset.
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
Hackable and optimized Transformers building blocks, supporting a composable construction.
Chapter by Chapter notes, exercises and code for a variety of machine learning books using Python
Code and slides for the "SOLID principles for ML engineers" series on The Sound of AI YouTube channel.
Preprocessing pipeline on Brain MR Images through FSL and ANTs, including registration, skull-stripping, bias field correction, enhancement and segmentation.
Models and examples built with TensorFlow
DeepLabv3+ built in TensorFlow
A template for scikit-learn extensions
Automatic extraction of relevant features from time series:
A library for debugging/inspecting machine learning classifiers and explaining their predictions
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphic…
A game theoretic approach to explain the output of any machine learning model.
Applying machine learning to predict loan charge-offs on LendingClub.com
A prediction of D+1 stock prices based on neural network models
A simple python implementation of Fuzzy C-means algorithm.