attempt at organising some of the useful repos I found around github
The code from the Machine Learning Bookcamp book
Work related to time series prediction and forecasting of Coronavirus
Today I learnt
Bayesian Data Analysis course at Aalto
Statistical Rethinking Course Winter 2020/2021
Complete deep learning project developed in Full Stack Deep Learning, Spring 2021
Draft of the fastai book
code and experiments I am doing while going through fastai's book
testing github actions to do crazy things
for stashing various experiments around the manning 3d-medical-image-analysis-with-pytorch project
attempt to create an full fledge spacenet building segmentation model that also does inference
Image processing in Python
napari: a fast, interactive, multi-dimensional image viewer for python
repo for the manning Monitoring Changes in Surface Water Using Satellite Image Data project
Code and associated files for the deploying ML models within AWS SageMaker
Case studies, examples, and exercises for learning to deploy ML models using AWS SageMaker.
DL PyTorch library for time series forecasting (originally for flood forecasting)
A django website used in the book Practical Recommender Systems to illustrate how recommender algorithms can be implemented.
A course on causal machine learning.
some code from the old phd days
"Help us understand how geography affects virality."
Supervised classification of Study designs
"What is known about transmission, incubation, and environmental stability?"
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
experiments with building identification in spacenet challenge datasets