Pinned Repositories
30DayChartChallenge
Contributions to the #30DayChartChallenge
aml4td-website
Website sources for Applied Machine Learning for Tabular Data
Bayesian-HMM
A non-parametric Bayesian approach to Hidden Markov Models
bbr
Biostatistics for Biomedical Research
catch22
catch-22: CAnonical Time-series CHaracteristics
cocktail-party-problem
BioCPPNet: Automatic Bioacoustic Source Separation with Deep Neural Networks
data-screencasts
Code from live exploratory analyses of data in R
electron-quick-start
Clone to try a simple Electron app
example-code-2e
Example code for Fluent Python, 2nd edition (O'Reilly 2022)
f1tenth_racetracks
This repository contains maps from over 20 real race tracks (mainly F1 and DTM) downscaled for the usage in the F1TENTH Gym and F1TENTH Simulator.
chrisdissanayake's Repositories
chrisdissanayake/30DayChartChallenge
Contributions to the #30DayChartChallenge
chrisdissanayake/aml4td-website
Website sources for Applied Machine Learning for Tabular Data
chrisdissanayake/Bayesian-HMM
A non-parametric Bayesian approach to Hidden Markov Models
chrisdissanayake/bbr
Biostatistics for Biomedical Research
chrisdissanayake/catch22
catch-22: CAnonical Time-series CHaracteristics
chrisdissanayake/cocktail-party-problem
BioCPPNet: Automatic Bioacoustic Source Separation with Deep Neural Networks
chrisdissanayake/data-screencasts
Code from live exploratory analyses of data in R
chrisdissanayake/electron-quick-start
Clone to try a simple Electron app
chrisdissanayake/example-code-2e
Example code for Fluent Python, 2nd edition (O'Reilly 2022)
chrisdissanayake/f1tenth_racetracks
This repository contains maps from over 20 real race tracks (mainly F1 and DTM) downscaled for the usage in the F1TENTH Gym and F1TENTH Simulator.
chrisdissanayake/garage_phm
chrisdissanayake/gsoc17-hhmm
Bayesian Hierarchical Hidden Markov Models applied to financial time series, a research replication project for Google Summer of Code 2017.
chrisdissanayake/industry-machine-learning
A curated list of applied machine learning and data science notebooks and libraries across different industries (by @firmai)
chrisdissanayake/ISLR-python
An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code
chrisdissanayake/Kats
Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics, detecting change points and anomalies, to forecasting future trends.
chrisdissanayake/LearningMPC
Learning based Model Prodictive Control for online iterative trajectory optimization for F1/10 autonomous racing.
chrisdissanayake/Machine-Learning-for-Asset-Managers
Implementation of code snippets, exercises and application to live data from Machine Learning for Asset Managers (Elements in Quantitative Finance) written by Prof. Marcos López de Prado.
chrisdissanayake/manuscript-template
chrisdissanayake/mlfinlab
MlFinLab helps portfolio managers and traders who want to leverage the power of machine learning by providing reproducible, interpretable, and easy to use tools.
chrisdissanayake/MoonRocket3D
3D files of a famous comics character moon rocket
chrisdissanayake/Non-linear-dynamics-Strogatz
Python scripts connected to Strogatz's nonlinear dynamics and chaos theory text.
chrisdissanayake/photon
RStudio Add-in to build Shiny apps utilizing the Electron framework
chrisdissanayake/prophet
Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
chrisdissanayake/SurfaceTopography
Read and analyze surface topographies
chrisdissanayake/tsfeatures
Time series features