Charlie Lew's repositories
pytorch-tutorial
PyTorch Tutorial for Deep Learning Researchers
EKF_for_Aircraft_Dynamics-
Extended Kalman Filter for aircraft dynamics
pybnn
Bayesian neural network package
Awesome-Graph-Neural-Networks
Paper Lists for Graph Neural Networks
edgebundle
R package implementing edge bundling algorithms
GNNPapers
Must-read papers on graph neural networks (GNN)
CFDPython
A sequence of Jupyter notebooks featuring the "12 Steps to Navier-Stokes" http://lorenabarba.com/
assignment
Assignments and Graders for Discrete Optimization on Coursera
acm-dec-2020-nlp
Natural Language Processing using PyTorch
bayesian-machine-learning
Notebooks about Bayesian methods for machine learning
azureml-examples
Official community-driven Azure Machine Learning Examples, tested with GitHub Actions
graph-neural-networks-1
Library to implement graph neural networks in PyTorch
benchmarking-gnns
Repository for benchmarking graph neural networks
holoviews
With Holoviews, your data visualizes itself.
azure-mol-samples-2nd-ed
Supporting resources for "Learn Azure in a Month of Lunches - 2nd edition" (Manning Publications)
PolyFuzz
Fuzzy string matching, grouping, and evaluation.
Fraud-Detection-Credit-Card-Account-Origination
This project commissions to examine the 100,000 credit card application data, detect abnormality and potential fraud in the dataset. All data manipulation and analysis are conducted in R. Featured analysis methods include Principal Component Analysis (PCA), Heuristic Algorithm and Autoencoder.
fable
Tidy time series forecasting
forecast
forecast package for R
docker-stylegan2-ada
My Docker image for running Stylegan2 ADA with GPU
resources
PyMC3 educational resources
Awesome-Bioinformatics
A curated list of awesome Bioinformatics libraries and software.
tensorflow_macos
TensorFlow for macOS 11.0+ accelerated using Apple's ML Compute framework.
Portfolio
This section consists of projects that i have completed during my srudies in datacamp. There are some jupyter
data-science-from-scratch-1
code for Data Science From Scratch book
sublime-monokai-free
A beautiful, modern, high quality, Monokai theme for Sublime Text 3.
GraphNeuralNetwork
Implementation and experiments of graph neural netwokrs, like gcn,graphsage,gat,etc.
LSTM-Neural-Network-for-Time-Series-Prediction
LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data
recommenders
Best Practices on Recommendation Systems
recmetrics
A library of metrics for evaluating recommender systems