Statsmodels: statistical modeling and econometrics in Python

Introducing neural networks to predict stock prices

Some experiments about Machine Learning

A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.

BAyesian Model-Building Interface (Bambi) in Python.

This package can be used for dominance analysis or Shapley Value Regression for finding relative importance of predictors on given dataset. This library can be used for key driver analysis or marginal resource allocation models.

Time series prediction with Sequential Model and LSTM units

A Trading Model Utilizing a Dynamic Weighting and Aggregate Scoring System with LSTM Networks

A Python library for moderation, mediation and conditional process analysis.

A python class for enhancing the spatial resolution of satellite-derived Land Surface Temperatures (LST) using statistical downscaling.

Implementation of Query-guided Regression Network with Context Policy for Phrase Grounding in Tensorflow

The repository contains python codes, which I have developed as the facilitator of the two consecutive Deep Learning Workshops (I and II) for the master's students of computer science, University of Windsor.

a collection of modern sparse (regularized) linear regression algorithms.

Machine Learning Model to predict the payment date of an invoice when it gets created in the system.

Examining how large language models (LLMs) perform across various synthetic regression tasks when given (input, output) examples in their context, without any parameter update

Applied Econometrics Library for Python

Top 1% rankings (22/3270) code sharing for Kaggle competition Sberbank Russian Housing Market: https://www.kaggle.com/c/sberbank-russian-housing-market

In this project we are comparing various regression models to find which model works better for predicting the AQI (Air Quality Index).