jerryji1993

DNABERT

DNABERT: pre-trained Bidirectional Encoder Representations from Transformers model for DNA-language in genome

kidGAN

kidGAN to generate children/babies images based on input of parents pictures

MetMCC-SCAN

Predicting metastasis of Merkel Cell Carcinoma

sradownload_star_rsem

My script for SRAdownload-STAR-RSEM pipeline for transcriptome analysis

wikiart_style_classification

Machine: The New Art Connoisseur (https://arxiv.org/abs/1911.10091)

bayesian-stat-machine-learning

"Bayesian Statistics & Machine Learning" Reading Group at Northwestern Statistics

bootcamp-2018

Materials for 2018 MSiA Boot Camp

efficientnet_pytorch

EfficientNet implemented in Pytorch with SyncBatchNorm layers on multiple GPUs and memory optimization trick for my Kaggle competitions. Code modified from https://github.com/lukemelas/EfficientNet-PyTorch/.

isoform_drug_targets

In silico analysis of alternative splicing on drug-target gene interactions

PUBG_winner_prediction

PUBG Finish Placement Prediction project from Kaggle competition

caret

caret (Classification And Regression Training) R package that contains misc functions for training and plotting classification and regression models

Clinical-Trial-Parser

Library for converting clinical trial eligibility criteria to a machine-readable format.

databases_workshop

RCS Intro to Databases workshop materials

diceR

Diverse Cluster Ensemble in R

EMpire

Isoform-level quantification of ribosome-footprint and proteomic data

flask-project

Introduction-to-Python-Programming-and-Data-Science

Introduction to Python Programming and Data Science

jerryji1993.github.io

keras-squeeze-excite-network

Implementation of Squeeze and Excitation Networks in Keras

mlrefined

Jupyter notebooks, Python and MATLAB code examples, and demos from the textbook "Machine Learning Refined" (Cambridge University Press). See our blog https://jermwatt.github.io/mlrefined/index.html for interactive versions of many of the notebooks in this repo.

MSIA-D3Course-2019

proteinnet

Standardized data set for machine learning of protein structure

rgn

Recurrent Geometric Networks for end-to-end differentiable learning of protein structure