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pctskate's Projects

awesome-python icon awesome-python

A curated list of awesome Python frameworks, libraries and software.

chiro icon chiro

Public Implementation of ChIRo from "Learning 3D Representations of Molecular Chirality with Invariance to Bond Rotations"

clinical-trial-outcome-prediction icon clinical-trial-outcome-prediction

benchmark dataset and Deep learning method (Hierarchical Interaction Network, HINT) for clinical trial approval probability prediction, accepted by Cell Patterns 2022.

deepchem icon deepchem

Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology

example-code icon example-code

Example code for the book Fluent Python, 1st Edition (O'Reilly, 2015)

fastai icon fastai

The fastai deep learning library

gsn icon gsn

Official repository for the paper "Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting" (TPAMI'22) https://arxiv.org/abs/2006.09252

handson-ml2 icon handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

mat icon mat

The official implementation of the Molecule Attention Transformer.

ml-ensemble-docking icon ml-ensemble-docking

Improving Structure-Based Virtual Screening with Ensemble Docking and Machine Learning

mmpdb_v3.1 icon mmpdb_v3.1

A package to identify matched molecular pairs and use them to predict property changes.

mol2vec icon mol2vec

Mol2vec - an unsupervised machine learning approach to learn vector representations of molecular substructures

nmp_qc icon nmp_qc

Neural Message Passing for Computer Vision

paddlehelix icon paddlehelix

Bio-Computing Platform Featuring Large-Scale Representation Learning and Multi-Task Deep Learning “螺旋桨”生物计算工具集

pcc icon pcc

Resources for Python Crash Course, from No Starch Press.

procare icon procare

ProCare: A Point Cloud Registration Approach to Align Protein Cavities

pydata-book icon pydata-book

Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media

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