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alphamissense

andrew-ng-notes

This is Andrew NG Coursera Handwritten Notes.

awesome-python-data-science

A curated list of Python libraries used for data science.

bash_search

Blazingly fast and interactive file search scripts, based on FZF and BASH.

best-readme-template

An awesome README template to jumpstart your projects!

clinvar-miner

Website to analyze conflicting assertions in ClinVar

colabdesign

Making Protein Design accessible to all via Google Colab!

colabfold

Making Protein folding accessible to all!

cookiecutter-data-science

A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.

coursera-deep-learning-specialization

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks;

cpt

Cross-protein transfer learning for variant effect prediction

deep-learning-specialization

Coursera : Deep Learning Specialization by Andrew Ng

deeplearning-notes

Notes for Deep Learning Specialization Courses led by Andrew Ng.

dtu_mlops

Exercises and supplementary material for the machine learning operations course at DTU.

dtu_mlops_mnist

dtu_mlops_s1_final_exercise

dtu_mlops_vxh357

This repository is a modified version of the DTU Machine Learning Operations course materials, featuring my personal solutions. Originally git cloned from https://github.com/SkafteNicki/dtu_mlops

esm

Evolutionary Scale Modeling (esm): Pretrained language models for proteins

esm-variants

evcouplings

Evolutionary couplings from protein and RNA sequence alignments

eve

Official repository for the paper "Large-scale clinical interpretation of genetic variants using evolutionary data and deep learning". Joint collaboration between the Marks lab and the OATML group.

evmutation

Mutation effects predicted from sequence co-variation

evzoom

Visually explore covariation in protein families

gcp_docker_example

git-commit-message

Git commit message: how to write a great git commit message and commit template for version control

gremlin

GREMLIN is a method to learn a statistical model of a protein family that captures both conservation and co-evolution patterns in the family. The strength of measured co-evolution is strongly predictive of residue-residue contacts in the 3D structure of the protein.

hgvs

Python library to parse, format, validate, normalize, and map sequence variants. `pip install hgvs`

kull_prism

Software development pipelines related to the PRISM project

machine-learning-specialization-coursera

Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG

ml-course-notes

🎓 Sharing machine learning course / lecture notes.