Rebuilding https://github.com/mac-theobio/McMasterPandemic/

Model manipulation and fitting library based on TensorFlow and optimised for simple and direct manipulation of probability density functions. Its main focus is on scalability, parallelisation and user friendly experience.

Python-based fitting of 1-state MDP Reinforcement Learning algorithms using Global Optimization (Turner Lab, HHMI, 2023)

a gradient-based optimisation routine for highly parameterised non-linear dynamical models

SourceXtractor++, the next generation SExtractor

JetSeT a framework for self-consistent modeling and fitting of astrophysical relativistic jets

Solution in the form of a tutorial article wherein the key decisions made in conducting a CFA are validated through recent literature and presented within a dynamic document framework.

Labs for the "Statistical Learning and Neural Networks" course @ Polytechnic University of Turin

piecewise-regression (aka segmented regression) in python. For fitting straight line models to data with one or more breakpoints where the gradient changes.

C++ Tool for Template Fitting for Photometric Redshift Estimation

Multiple linear regression model based on eCommerce customers data in Python language.

step-by-step walkthrough of model fitting via least squares and staircase validation via negative log likelihood in MATLAB

Package for fitting/optimization of NeuroML models

torchbearer: A model fitting library for PyTorch

An R package of S3 generic methods for Bayesian analyses that generate MCMC samples

A lean C++ library for working with point cloud data

This project will use time series analysis to forecast the exchange rate between the euro and the US dollar. The project will use a variety of statistical techniques, such as ARIMA to model the data and forecast the exchange rate.

This project will use time series analysis to forecast the exchange rate between the euro and the US dollar. The project will use a variety of statistical techniques, such as ARIMA to model the data and forecast the exchange rate.

Develop a data science project using historical sales data to build a regression model that accurately predicts future sales. Preprocess the dataset, conduct exploratory analysis, select relevant features, and employ regression algorithms for model development. Evaluate model performance, optimize hyperparameters, and provide actionable insights.

Wrangled real estate data from multiple sources and file formats, brought it into a single consistent form and analysed the results.