Robyn is an experimental, AI/ML-powered and open sourced Marketing Mix Modeling (MMM) package from Meta Marketing Science. Our mission is to democratise modeling knowledge, inspire the industry through innovation, reduce human bias in the modeling process & build a strong open source marketing science community.

A Julia package for multivariate statistics and data analysis (e.g. dimension reduction)

👩🏻‍⚕️Covid-19 estimation and forecast using statistical model; 新型冠状病毒肺炎统计模型预测 (Jan 2020)

Python machine learning applications in image processing, recommender system, matrix completion, netflix problem and algorithm implementations including Co-clustering, Funk SVD, SVD++, Non-negative Matrix Factorization, Koren Neighborhood Model, Koren Integrated Model, Dawid-Skene, Platt-Burges, Expectation Maximization, Factor Analysis, ISTA, F…

A simple machine learning framework written in Swift 🤖

Predicting Amsterdam house / real estate prices using Ordinary Least Squares-, XGBoost-, KNN-, Lasso-, Ridge-, Polynomial-, Random Forest-, and Neural Network MLP Regression (via scikit-learn)

Implemented ADMM for solving convex optimization problems such as Lasso, Ridge regression

Objective of the repository is to learn and build machine learning models using Pytorch. 30DaysofML Using Pytorch

Built house price prediction model using linear regression and k nearest neighbors and used machine learning techniques like ridge, lasso, and gradient descent for optimization in Python

Generalized Linear Regressions Models (penalized regressions, robust regressions, ...)

A MATLAB package for modelling multivariate stimulus-response data

By-hand code for models and algorithms. An update to the 'Miscellaneous-R-Code' repo.

次元期权应征面试题范例。

Analyzes weightlifting videos for correct posture using pose estimation with OpenCV

A Julia package for robust regressions using M-estimators and quantile regressions

Automated Essay Scoring on The Hewlett Foundation dataset on Kaggle

Demo from Data Community Bydgoszcz i Toruń, 27.02.2019

Double Descent Curve with Optical Random Features

Repository containing introduction to the main methods and models used in machine learning problems of regression, classification and clustering.

Python notebooks for my graduate class on Detection, Estimation, and Learning. Intended for in-class demonstration. Notebooks illustrate a variety of concepts, from hypothesis testing to estimation to image denoising to Kalman filtering. Feel free to use or modify for your instruction or self-study.