Case studies with Bayesian methods

Overview

bayesian-modeling

Case studies with Bayesian methods

Hierarchical model for spelling performance

A hierarchical model for the spelling data from the study D. Thissen, Steinberg, and Wainer (1993)

average actor rates

Multinomial logistic model for three-class classifition

A multinomial logistic model for the iris dataset (Fisher, 1936)

sepal evaluation

Fourier analysis for time series

A Fourier analysis model for the Mauna Loa CO2 data (the Keeling curve)

keeling curve

Time series modeling with heteroskedastic data

A hierarchical time series model with log-normal likelihood for air polution data in Skopje.

log-normal time-series

Inference with weights on observed data

A simple example using Potential for inference with data with weights

large poisson dataset

Monotone dependency modeling

A simple example using Dirichlet prior for modeling of monotone dependency

monotone dependency

Slow evolving multiplicative factor - Covid-19 Rt model

A model for estimation of the Rt reproductive factor for Covid-19, modeled with Random walks in the log scale.

covid 19 Rt factor

Owner
Baze Petrushev
Data Scientist playing around with Python and Spark
Baze Petrushev
Fast Fourier Transform-accelerated Interpolation-based t-SNE (FIt-SNE)

FFT-accelerated Interpolation-based t-SNE (FIt-SNE) Introduction t-Stochastic Neighborhood Embedding (t-SNE) is a highly successful method for dimensi

Kluger Lab 547 Dec 21, 2022
Provide an input CSV and a target field to predict, generate a model + code to run it.

automl-gs Give an input CSV file and a target field you want to predict to automl-gs, and get a trained high-performing machine learning or deep learn

Max Woolf 1.8k Jan 04, 2023
NCVX (NonConVeX): A User-Friendly and Scalable Package for Nonconvex Optimization in Machine Learning.

NCVX (NonConVeX): A User-Friendly and Scalable Package for Nonconvex Optimization in Machine Learning.

SUN Group @ UMN 28 Aug 03, 2022
Xeasy-ml is a packaged machine learning framework.

xeasy-ml 1. What is xeasy-ml Xeasy-ml is a packaged machine learning framework. It allows a beginner to quickly build a machine learning model and use

9 Mar 14, 2022
A simple python program that draws a tree for incrementing values using the Collatz Conjecture.

Collatz Conjecture A simple python program that draws a tree for incrementing values using the Collatz Conjecture. Values which can be edited: Length

davidgasinski 1 Oct 28, 2021
CD) in machine learning projectsImplementing continuous integration & delivery (CI/CD) in machine learning projects

CML with cloud compute This repository contains a sample project using CML with Terraform (via the cml-runner function) to launch an AWS EC2 instance

Iterative 19 Oct 03, 2022
Data Efficient Decision Making

Data Efficient Decision Making

Microsoft 197 Jan 06, 2023
Predict the output which should give a fair idea about the chances of admission for a student for a particular university

Predict the output which should give a fair idea about the chances of admission for a student for a particular university.

ArvindSandhu 1 Jan 11, 2022
Hypernets: A General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.

A General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.

DataCanvas 216 Dec 23, 2022
My project contrasts K-Nearest Neighbors and Random Forrest Regressors on Real World data

kNN-vs-RFR My project contrasts K-Nearest Neighbors and Random Forrest Regressors on Real World data In many areas, rental bikes have been launched to

1 Oct 28, 2021
Climin is a Python package for optimization, heavily biased to machine learning scenarios

climin climin is a Python package for optimization, heavily biased to machine learning scenarios distributed under the BSD 3-clause license. It works

Biomimetic Robotics and Machine Learning at Technische Universität München 177 Sep 02, 2022
Anomaly Detection and Correlation library

luminol Overview Luminol is a light weight python library for time series data analysis. The two major functionalities it supports are anomaly detecti

LinkedIn 1.1k Jan 01, 2023
Automated Machine Learning with scikit-learn

auto-sklearn auto-sklearn is an automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator. Find the documentation here

AutoML-Freiburg-Hannover 6.7k Jan 07, 2023
This is a Cricket Score Predictor that predicts the first innings score of a T20 Cricket match using Machine Learning

This is a Cricket Score Predictor that predicts the first innings score of a T20 Cricket match using Machine Learning. It is a Web Application.

Developer Junaid 3 Aug 04, 2022
This is the code repository for LRM Stochastic watershed model.

LRM-Squannacook Input data for generating stochastic streamflows are observed and simulated timeseries of streamflow. their format needs to be CSV wit

1 Feb 14, 2022
dirty_cat is a Python module for machine-learning on dirty categorical variables.

dirty_cat dirty_cat is a Python module for machine-learning on dirty categorical variables.

637 Dec 29, 2022
Projeto: Machine Learning: Linguagens de Programacao 2004-2001

Projeto: Machine Learning: Linguagens de Programacao 2004-2001 Projeto de Data Science e Machine Learning de análise de linguagens de programação de 2

Victor Hugo Negrisoli 0 Jun 29, 2021
icepickle is to allow a safe way to serialize and deserialize linear scikit-learn models

icepickle It's a cooler way to store simple linear models. The goal of icepickle is to allow a safe way to serialize and deserialize linear scikit-lea

vincent d warmerdam 24 Dec 09, 2022
Pragmatic AI Labs 421 Dec 31, 2022
Data Version Control or DVC is an open-source tool for data science and machine learning projects

Continuous Machine Learning project integration with DVC Data Version Control or DVC is an open-source tool for data science and machine learning proj

Azaria Gebremichael 2 Jul 29, 2021