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
Kaggler is a Python package for lightweight online machine learning algorithms and utility functions for ETL and data analysis.

Kaggler is a Python package for lightweight online machine learning algorithms and utility functions for ETL and data analysis. It is distributed under the MIT License.

Jeong-Yoon Lee 720 Dec 25, 2022
jaxfg - Factor graph-based nonlinear optimization library for JAX.

Factor graphs + nonlinear optimization in JAX

Brent Yi 134 Dec 21, 2022
Bayesian Modeling and Computation in Python

Bayesian Modeling and Computation in Python Open access and Code This repository contains the open access version of the text and the code examples in

Bayesian Modeling and Computation in Python 339 Jan 02, 2023
Open source time series library for Python

PyFlux PyFlux is an open source time series library for Python. The library has a good array of modern time series models, as well as a flexible array

Ross Taylor 2k Jan 02, 2023
Mixing up the Invariant Information clustering architecture, with self supervised concepts from SimCLR and MoCo approaches

Self Supervised clusterer Combined IIC, and Moco architectures, with some SimCLR notions, to get state of the art unsupervised clustering while retain

Bendidi Ihab 9 Feb 13, 2022
High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.

What is xLearn? xLearn is a high performance, easy-to-use, and scalable machine learning package that contains linear model (LR), factorization machin

Chao Ma 3k Jan 08, 2023
Winning solution for the Galaxy Challenge on Kaggle

Winning solution for the Galaxy Challenge on Kaggle

Sander Dieleman 483 Jan 02, 2023
Predict profitability of trades based on indicator buy / sell signals

Predict profitability of trades based on indicator buy / sell signals Trade profitability analysis for trades based on various indicators signals: MAC

Tomasz Porzycki 1 Dec 15, 2021
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
Tangram makes it easy for programmers to train, deploy, and monitor machine learning models.

Tangram Website | Discord Tangram makes it easy for programmers to train, deploy, and monitor machine learning models. Run tangram train to train a mo

Tangram 1.4k Jan 05, 2023
Graphsignal is a machine learning model monitoring platform.

Graphsignal is a machine learning model monitoring platform. It helps ML engineers, MLOps teams and data scientists to quickly address issues with data and models as well as proactively analyze model

Graphsignal 143 Dec 05, 2022
A python library for easy manipulation and forecasting of time series.

Time Series Made Easy in Python darts is a python library for easy manipulation and forecasting of time series. It contains a variety of models, from

Unit8 5.2k Jan 04, 2023
JMP is a Mixed Precision library for JAX.

Mixed precision training [0] is a technique that mixes the use of full and half precision floating point numbers during training to reduce the memory bandwidth requirements and improve the computatio

DeepMind 108 Dec 31, 2022
Machine Learning Algorithms ( Desion Tree, XG Boost, Random Forest )

implementation of machine learning Algorithms such as decision tree and random forest and xgboost on darasets then compare results for each and implement ant colony and genetic algorithms on tsp map,

Mohamadreza Rezaei 1 Jan 19, 2022
pymc-learn: Practical Probabilistic Machine Learning in Python

pymc-learn: Practical Probabilistic Machine Learning in Python Contents: Github repo What is pymc-learn? Quick Install Quick Start Index What is pymc-

pymc-learn 196 Dec 07, 2022
Forecast dynamically at scale with this unique package. pip install scalecast

🌄 Scalecast: Dynamic Forecasting at Scale About This package uses a scaleable forecasting approach in Python with common scikit-learn and statsmodels

Michael Keith 158 Jan 03, 2023
MIT-Machine Learning with Python–From Linear Models to Deep Learning

MIT-Machine Learning with Python–From Linear Models to Deep Learning | One of the 5 courses in MIT MicroMasters in Statistics & Data Science Welcome t

2 Aug 23, 2022
A comprehensive repository containing 30+ notebooks on learning machine learning!

A comprehensive repository containing 30+ notebooks on learning machine learning!

Jean de Dieu Nyandwi 3.8k Jan 09, 2023
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