Pinned Repositories
nameguess
3d_convolution_neural_net_MNET
Keras Implementation of 3d Convolutional Neural Network
COVID-19
Novel Coronavirus (COVID-19) Cases, provided by JHU CSSE
COVID19_US_databricks
A Study on Correlation of Conty-Wide US Demographics and Economy on COVID-19 Pandemic. The COVID-19 data is from JHU CSSE, and US demographics data is from US Census Bureau.
Ecommerce_Prod_Rev_NLP
In this project, using the dataset from Amazon Customer Review (https://registry.opendata.aws/amazon-reviews/), unsupervised learning models are applied to automatically analyze the underlying structures of user reviews on grocery products, and to visualize the results by multiple natural language processing (NLP) models/tools.
FTCNN
CNN for structure classification through Fourier Transform of voxelized point clouds
pointnet.phasedetection
This repo uses PointNet [1](https://arxiv.org/abs/1612.00593), a neural network designed for computer vision applications using point clouds. In this study, a properly-trained PointNet was demonstrated to be highly generalizable on morphology detection in molecular simulations, and can be potentially extended to discovery of emerging ordered patterns from non-equilibrium systems.
QGforQA
sf_crime_analysis
In this Databricks notebook, Spark SQL and dataframe was used for big data analysis and OLAP on SF crime data. (https://data.sfgov.org/Public-Safety/Police-Department-Incident-Reports-Historical-2003/tmnf-yvry).
structure_factor
Calculate average structure factor from pdb files. Implemented CPU-based parallelization using numba and cuda-acceleration by Taichi. Codes belongs to Siepmann Group, University of Minnesota. Author of original code: Paul Qile Chen. Contributors: Don Zhengyuan Shen; Andrew Yangzesheng Sun
donshen's Repositories
donshen/pointnet.phasedetection
This repo uses PointNet [1](https://arxiv.org/abs/1612.00593), a neural network designed for computer vision applications using point clouds. In this study, a properly-trained PointNet was demonstrated to be highly generalizable on morphology detection in molecular simulations, and can be potentially extended to discovery of emerging ordered patterns from non-equilibrium systems.
donshen/FTCNN
CNN for structure classification through Fourier Transform of voxelized point clouds
donshen/COVID19_US_databricks
A Study on Correlation of Conty-Wide US Demographics and Economy on COVID-19 Pandemic. The COVID-19 data is from JHU CSSE, and US demographics data is from US Census Bureau.
donshen/Ecommerce_Prod_Rev_NLP
In this project, using the dataset from Amazon Customer Review (https://registry.opendata.aws/amazon-reviews/), unsupervised learning models are applied to automatically analyze the underlying structures of user reviews on grocery products, and to visualize the results by multiple natural language processing (NLP) models/tools.
donshen/sf_crime_analysis
In this Databricks notebook, Spark SQL and dataframe was used for big data analysis and OLAP on SF crime data. (https://data.sfgov.org/Public-Safety/Police-Department-Incident-Reports-Historical-2003/tmnf-yvry).
donshen/QGforQA
donshen/structure_factor
Calculate average structure factor from pdb files. Implemented CPU-based parallelization using numba and cuda-acceleration by Taichi. Codes belongs to Siepmann Group, University of Minnesota. Author of original code: Paul Qile Chen. Contributors: Don Zhengyuan Shen; Andrew Yangzesheng Sun
donshen/3d_convolution_neural_net_MNET
Keras Implementation of 3d Convolutional Neural Network
donshen/COVID-19
Novel Coronavirus (COVID-19) Cases, provided by JHU CSSE
donshen/Kaggle_Bank_Customer_Churn
In this project, using the dataset from Kaggle (https://www.kaggle.com/adammaus/predicting-churn-for-bank-customers), different supervised learning models are used to predict customers that are likely to churn in the future. Top factors that influence user retention are analyzed.
donshen/CS224W-Colab
Solutions for CS224W Winter 2021 Colab
donshen/CSCI5751
Local dynamoDB
donshen/CSCI5751_Project2_dymz
donshen/Data-Structure-and-Performance
donshen/dvc
🦉Data Version Control | Git for Data & Models
donshen/image_classification_resnet
donshen/ML-NLP
此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现,也是作为一个算法工程师必会的理论基础知识。
donshen/Multi-Variate-Models-on-London-BikeSharing-Data
donshen/neural_question_generation
Implementation of <Learning to Ask: Neural Question Generation for Reading Comprehension> by Xinya Du et al.
donshen/NLP_course_material
Notes and codes from the NLP-related contents for the course: https://courses.d2l.ai/zh-v2/ by Mu Li
donshen/packmol
Packmol
donshen/ParlAI
A framework for training and evaluating AI models on a variety of openly available dialogue datasets.
donshen/pointnet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
donshen/Python
:snake: Python Programs
donshen/pytorch-pretrained-BERT
📖The Big-&-Extending-Repository-of-Transformers: Pretrained PyTorch models for Google's BERT, OpenAI GPT & GPT-2, Google/CMU Transformer-XL.
donshen/question_generation
Neural question generation using transformers
donshen/tapas
End-to-end neural table-text understanding models.
donshen/Time-Series-Analysis-in-R
Problems worked out from the book Time Series Analysis and Its Applications: With R Examples by Shumway and Stoffer. Includes brief time series overview, time series regression, and ARIMA modeling.
donshen/topic_segmenter
Tool for segmenting group chat conversations using NLP and Neural Networks