regression-algorithms

The first machine learning framework that encourages learning ML concepts instead of memorizing class functions.

A repository for implementation of artificial intelligence algorithm which includes machine learning and deep learning algorithm as well as classical AI search algorithm

A memory efficient GBDT on adaptive distributions. Much faster than LightGBM with higher accuracy. Implicit merge operation.

Implementation of a Partial Least Squares Regressor

Using machine learning algorithms to predict first innings score in limited overs cricket matches

Machine learning Regression problem with easy understandable solutions

This repository is for every beginner who just finished with the theoretical part of Machine Learning and wants to have a hands on experience of various kinds of algorithm and make predictions on a real time dataset.

Estimation and inference from generalized linear models using explicit and implicit methods for bias reduction

My implementation of the regression algorithms

This repository provides a Python3 Library with implementations of the Least-Squares Support Vector Machine (LS-SVM) machine learning model. The Classes are designed to integrate smoothly with the scikit-learn library.

In this repository you can find many different, small, projects which demonstrate regression techniques using python programming language

Visual regression testing made easy. Automating the boring stuff

The main aim of this project is to tell that the certain project will be successful or it will fail by applying machine learning algorithm. In this , LOGISTIC REGRESSION is used to determine the success of the project by splitting the data into training and testing models and predicting a successful one.

Sparse Spectrum Gaussian Process Regression

Notebooks and Python about data science

It is the repo I listed my kernels in Kaggle. You can access it in detail from my Kaggle address https://www.kaggle.com/bulentsiyah.

Moody's Bond Rating Classifier and USPHCI Economic Activity Forecast Modeling

A Linear Regression model to predict the car prices for the U.S market to help a new entrant understand important pricing variables in the U.S automobile industry. A highly comprehensive analysis with detailed explanation of all steps; data cleaning, exploration, visualization, feature selection, model building, evaluation & MLR assumptions validity.

R package for automatic hyper parameter tuning and ensembles with deep learning, gradient boosting machines, and random forests. Powered by h2o.

Git repository for IBM Professional Certification on Data Science

Movie Revenue & Ratings Prediction Using 5000 IMDB Movies [Python, Machine Learning, GitHub]

Jupyter notebook that outlines the process of creating a machine learning predictive model. Predicts the peak "Wins Shared" by the current draft prospects based on numerous features such as college stats, projected draft pick, physical profile and age. I try out multiple models and pick the best performing one for the data from my judgement.

Machine Learning Projects in Python. Examples of popular machine learning algorithms with interactive Jupyter code explained

This is repository about the MachineLaering Basics including all the Machine learning Algorithms

Matlab source code of the paper "D. Wu, Y. Yuan, J. Huang and Y. Tan*, Optimize TSK Fuzzy Systems for Regression Problems: Mini-Batch Gradient Descent with Regularization, DropRule and AdaBound (MBGD-RDA), IEEE Trans. on Fuzzy Systems, 28(5), pp. 1003-1015, 2020."

A Machine Learning project for Machine Learning Internship offered by InternshipStudio.

Regression with Python & R.

Training of a neural network for nonlinear regression prediction with TensorFlow and Keras API.