Scraping statistics, predicting NBA player performance with neural networks and boosting algorithms, and optimising lineups for Draft Kings with genetic algorithm. Capstone Project for Machine Learning Engineer Nanodegree by Udacity.

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

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.

Machine learning Regression problem with easy understandable solutions

My implementation of the regression algorithms

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.

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

Sparse Spectrum Gaussian Process Regression

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

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.

Notebooks and Python about data science

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

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.

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

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

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

Regression with Python & R.

Git repository for IBM Professional Certification on Data Science

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

We have used four regression algorithms to predict crime in the United States and have also developed prediction systems.

Deep Robust Regression Methods

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

Predicting the age of abalone using multiple regression in R

Linear, ridge, lasso and elastic net regression in Julia using a videogames sales dataset

Black-box spike and slab variational inference, example with linear models