#Regression-models
Showing 33 of 33 repositories tagged #regression-models, ranked by stars
Statsmodels: statistical modeling and econometrics in Python
2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.
A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.
Curso de Introducción a Machine Learning con Python
Statistical Inference via Data Science: A ModernDive into R and the Tidyverse
Introducing neural networks to predict stock prices
Machine Learning notebooks for refreshing concepts.
My journey to learn and grow in the domain of Machine Learning and Artificial Intelligence by performing the #100DaysofMLCode Challenge. Now supported by bright developers adding their learnings :+1:
The foundational library of the Morpheus data science framework
Website sources for Applied Machine Learning for Tabular Data
Una introduccion al analisis de datos con R y R Studio
Implement, demonstrate, reproduce and extend the results of the Risk articles 'Differential Machine Learning' (2020) and 'PCA with a Difference' (2021) by Huge and Savine, and cover implementation details left out from the papers.
A statistical framework that serves as a common interface to a large range of models
The Google Advanced Data Analytics Certificate contains information on how to use machine learning, predictive modeling, and experimental design to collect and analyze large amounts of data, and prepare for jobs like Senior Data Analyst and Junior Data Scientist.
A Python library for moderation, mediation and conditional process analysis.
A series of notebooks that introduce Machine Learning concepts with hands-on practice and its mathematics in brief.
Project for Predicting Algerian Forest Fires and Fire Weather Index Using Machine Learning with Python.
An introductory statistics course for social scientists, using Stata
This repository contains the code and datasets for creating the machine learning models in the research paper titled "Time-series forecasting of Bitcoin prices using high-dimensional features: a machine learning approach"
A new library for all of the newest ai algorithms
A repository for a machine learning project about developing a hybrid movie recommender system.
Basic statistical modelling examples.
免費數字驅動的數學模型人工智能 | 為你的數字規律建立數學模型 | C語言免安裝軟體
Complement the article 'Differential Machine Learning' (Huge & Savine, 2020), including mathematical proofs and important implementation details for production
En este proyecto de GitHhub podrás encontrar parte del material que utilizo para impartir las clases de Introducción a la Ciencia de Datos (Data Science) con Python.
Undergraduate thesis, Seoul National University Dept. of Economics — "Modeling Volatility and Risk Spillover Between the Financial Markets of US and China Using GARCH Value-at-Risk Forecasting and Granger Causality."
In this project we are comparing various regression models to find which model works better for predicting the AQI (Air Quality Index).
Moody's Bond Rating Classifier and USPHCI Economic Activity Forecast Modeling
This project focuses on predicting gold prices using historical data and machine learning techniques. It demonstrates a complete data science workflow, including data preprocessing, exploratory data analysis, feature engineering, model training, evaluation, and result visualization using Python.
Sensor data of a renowned power plant has given by a reliable source to forecast some feature. Initially the work has done with KNIME software. Now the goal is to do the prediction/forecasting with machine learning. The idea is to check the result of forecast with univariate and multivariate time series data. Regression method, Statistical method.
End to end implementation and deployment of Machine Learning Car Price Prediction using python, flask, gunicorn, scikit-Learn, etc. on Heroku web application platform.