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Name: Ding NING
Type: User
Bio: Ph.D. Student (thesis submitted). Have worked on deep learning, spatiotemporal data mining, AI for sciences, predictive modeling, and complex data processing.
Location: New Zealand
Name: Ding NING
Type: User
Bio: Ph.D. Student (thesis submitted). Have worked on deep learning, spatiotemporal data mining, AI for sciences, predictive modeling, and complex data processing.
Location: New Zealand
Scripts and Jupyter notebooks for the projects in the AWS AI and Machine Learning Scholarship Program, last updated 10/2023
Scripts for DeepRacer model attempts on Amazon Web Services, last updated 06/2023
A Jupyter notebook for exploratory data analysis on the CDEMRIS dataset, last updated 02/2021
A Jupyter notebook for brain tumor segmentation with CNNs and autoencoders from 3D MRI, last updated 04/2021
A Jupyter notebook for urban building segmentation with CNNs and autoencoders from high-resolution satellite images, last updated 06/2021
Scripts for practicing data mining, including supervised regression and classification and unsupervised clustering, and association, last updated 06/2020
Packages for practicing data structures, including complexity, stacks, queues, deques, lists, graphs, trees, hashing, recursion, sorting, and search, last updated 08/2022
Jupyter notebooks for practicing data wrangling, including manipulating tabular data, images, web data, and relational databases, last updated 10/2019
Scripts and Jupyter notebooks for practicing deep learning, including GD-based optimization, regularization, neural network basics, FCNs, CNNs, and autoencoders, last updated 09/2020
Jupyter notebooks for tutoring deep learning, last updated 05/2021
A package that converts geographic spatiotemporal grids into non-Euclidean graphs, last updated 02/2024
A package that converts geographic spatiotemporal grids into non-Euclidean graphs using a different method, last updated 03/2024
Scripts for generating an adjacency matrix from the GHCN (New Zealand only) dataset and visualization, last updated 02/2021
Jupyter notebooks for ocean temperature anomaly forecasting with GNNs and CNNs and data preprocessing from NetCDF multidimensional data, last updated 07/2022
Jupyter notebooks for exploratory research on GNNs, last updated 04/2022
Scripts for global monthly sea surface temperature and sea surface temperature anomaly forecasting with GraphSAGEs, plus auxiliary functions, data processing and result demonstration, last updated 02/2024
Scripts for ocean temperature anomaly forecasting with FCNs, CNNs, GNNs, and other model attempts, plus auxiliary functions, data preprocessing and result demonstration, last updated 03/2023
Scripts for practicing distributed computing with HDFS and Spark, including scalable data preprocessing, data analysis, and ML for classification and recommendation, last updated 05/2020
Scripts for practicing Python programming, including programming basics, I/O, iteration, modularization, programming styles, OOP, and GUI, last updated 11/2019
Scripts that implement several meshing methods on 1D arrays, last updated 09/2023
Miscellaneous items
A Jupyter notebook for exploratory data analysis on the MOANA Ocean dataset, last updated 05/2021
Scripts for practicing multivariate statistics, including multivariate normal distribution, multiple regression, PCA, FA, DA, and clustering, last updated 06/2020
NeuralODE for simple case
A script for exploratory research on neural ODEs, last updated 12/2021
A script that merges daily NOAA OI SST data netCDF files into one monthly data file, using the CDO commands, last updated 11/2023
Scripts for practicing text data analysis, including discourse analysis, data preprocessing, information extraction, topic modeling, text classification, and sentiment analysis, last updated 10/2019
Scripts for practicing time series, including time series basics, transformation, dependencies, stationarity, regression, decomposition, and ARIMA, last updated 11/2019
Scripts for a unified deep learning approach for marine heatwave forecasts, including imbalanced regression losses, and GNN, GNN-LSTM and diffusion-GNN models, plus auxiliary functions, data processing and result demonstration, continually updated
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Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.