Pinned Repositories
CatBoostLSS
An extension of CatBoost to probabilistic forecasting.
ML-in-Finance-I-case-study-forecasting-tax-avoidance-rates
paper_ul3_wozniak_wrzesinski
reproducible_research_project
roulette_simulator
Roulette simulator in Julia
spatial_econometric_project
trendecon
Create Long Daily Series from Google Trends
unsupervised-machine-learning-project-number-1
michaelwozniak's Repositories
michaelwozniak/ML-in-Finance-I-case-study-forecasting-tax-avoidance-rates
michaelwozniak/trendecon
Create Long Daily Series from Google Trends
michaelwozniak/CatBoostLSS
An extension of CatBoost to probabilistic forecasting.
michaelwozniak/paper_ul3_wozniak_wrzesinski
michaelwozniak/reproducible_research_project
michaelwozniak/roulette_simulator
Roulette simulator in Julia
michaelwozniak/spatial_econometric_project
michaelwozniak/unsupervised-machine-learning-project-number-1
michaelwozniak/distributionalnn
michaelwozniak/git2018
Website prepared for Girls do IT 2018 event
michaelwozniak/magapi-wrapper
Wrapper around Microsoft Academic Knowledge API to retrieve MAG data
michaelwozniak/ml1_project
michaelwozniak/ml2_tools
michaelwozniak/orbit
A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.
michaelwozniak/pythonsql_project
michaelwozniak/RegressionSteps
The three functions explained below work together to explore and present further actions and possibilities of linear regression models. My goal is to help users experiment with the explanatory variables of a linear regression model. As a result, these experiments will help the user reach conclusions about how the initial dependent variable will change, if one of the explanatory variables is changed as wished.
michaelwozniak/rit_preliminaries
michaelwozniak/RR_classes
Reproducible Research repo template
michaelwozniak/scrapy_ws
michaelwozniak/Stock-Prediction-Models
Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations
michaelwozniak/web_scraping
Web scraping project
michaelwozniak/XGBoostLSS
An extension of XGBoost to probabilistic forecasting
michaelwozniak/zmod_dynamic_programming
Repozytorium z programem rozwiązyjącym dwukryterialne zagadnienie alokacji za pomocą programowania dynamicznego. Autorami są: Michał Woźniak oraz Michał Wrzesiński z WNE UW.