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
customer churn prediction prevention in telecom industry using machine learning and survival analysis

Telco Customer Churn Prediction - Plotly Dash Application Description This dash application allows you to predict telco customer churn using machine l

Benaissa Mohamed Fayçal 3 Nov 20, 2021
PennyLane is a cross-platform Python library for differentiable programming of quantum computers

PennyLane is a cross-platform Python library for differentiable programming of quantum computers. Train a quantum computer the same way as a neural ne

PennyLaneAI 1.6k Jan 01, 2023
Turns your machine learning code into microservices with web API, interactive GUI, and more.

Turns your machine learning code into microservices with web API, interactive GUI, and more.

Machine Learning Tooling 2.8k Jan 02, 2023
Arquivos do curso online sobre a estatística voltada para ciência de dados e aprendizado de máquina.

Estatistica para Ciência de Dados e Machine Learning Arquivos do curso online sobre a estatística voltada para ciência de dados e aprendizado de máqui

Renan Barbosa 1 Jan 10, 2022
Machine Learning approach for quantifying detector distortion fields

DistortionML Machine Learning approach for quantifying detector distortion fields. This project is a feasibility study for training a surrogate model

Joel Bernier 1 Nov 05, 2021
GroundSeg Clustering Optimized Kdtree

ground seg and clustering based on kitti velodyne data, and a additional optimized kdtree for knn and radius nn search

2 Dec 02, 2021
A simple and lightweight genetic algorithm for optimization of any machine learning model

geneticml This package contains a simple and lightweight genetic algorithm for optimization of any machine learning model. Installation Use pip to ins

Allan Barcelos 8 Aug 10, 2022
A data preprocessing and feature engineering script for a machine learning pipeline is prepared.

FEATURE ENGINEERING Business Problem: A data preprocessing and feature engineering script for a machine learning pipeline needs to be prepared. It is

Pinar Oner 7 Dec 18, 2021
TIANCHI Purchase Redemption Forecast Challenge

TIANCHI Purchase Redemption Forecast Challenge

Haorui HE 4 Aug 26, 2022
Primitives for machine learning and data science.

An Open Source Project from the Data to AI Lab, at MIT MLPrimitives Pipelines and primitives for machine learning and data science. Documentation: htt

MLBazaar 65 Dec 29, 2022
LightGBM + Optuna: no brainer

AutoLGBM LightGBM + Optuna: no brainer auto train lightgbm directly from CSV files auto tune lightgbm using optuna auto serve best lightgbm model usin

Rishiraj Acharya 22 Dec 15, 2022
Transform ML models into a native code with zero dependencies

m2cgen (Model 2 Code Generator) - is a lightweight library which provides an easy way to transpile trained statistical models into a native code

Bayes' Witnesses 2.3k Jan 03, 2023
scikit-fem is a lightweight Python 3.7+ library for performing finite element assembly.

scikit-fem is a lightweight Python 3.7+ library for performing finite element assembly. Its main purpose is the transformation of bilinear forms into sparse matrices and linear forms into vectors.

Tom Gustafsson 297 Dec 13, 2022
A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.

pmdarima Pmdarima (originally pyramid-arima, for the anagram of 'py' + 'arima') is a statistical library designed to fill the void in Python's time se

alkaline-ml 1.3k Dec 22, 2022
Predicting Keystrokes using an Audio Side-Channel Attack and Machine Learning

Predicting Keystrokes using an Audio Side-Channel Attack and Machine Learning My

3 Apr 10, 2022
A Time Series Library for Apache Spark

Flint: A Time Series Library for Apache Spark The ability to analyze time series data at scale is critical for the success of finance and IoT applicat

Two Sigma 970 Jan 04, 2023
Interactive Web App with Streamlit and Scikit-learn that applies different Classification algorithms to popular datasets

Interactive Web App with Streamlit and Scikit-learn that applies different Classification algorithms to popular datasets Datasets Used: Iris dataset,

Samrat Mitra 2 Nov 18, 2021
🌲 Implementation of the Robust Random Cut Forest algorithm for anomaly detection on streams

🌲 Implementation of the Robust Random Cut Forest algorithm for anomaly detection on streams

Real-time water systems lab 416 Jan 06, 2023
Given the names and grades for each student in a class N of students, store them in a nested list and print the name(s) of any student(s) having the second lowest grade.

Hackerank-Nested-List Given the names and grades for each student in a class N of students, store them in a nested list and print the name(s) of any s

Sangeeth Mathew John 2 Dec 14, 2021
Used Logistic Regression, Random Forest, and XGBoost to predict the outcome of Search & Destroy games from the Call of Duty World League for the 2018 and 2019 seasons.

Call of Duty World League: Search & Destroy Outcome Predictions Growing up as an avid Call of Duty player, I was always curious about what factors led

Brett Vogelsang 2 Jan 18, 2022