Compilation of cheatsheets related to AI, Machine Learning, Software Development, etc

Analyzing transactions of a retailer to predict promotional items.

Repository for mainly R tips and tricks for my blog. I also include some VBA, SQL, C and Linux Usage.

Template for data science projects (R-based) which includes a few useful utilities.

This repository contains the implementation of the research paper tVelloso, E., Bulling, A., Gellersen, H., Ugulino, W. and Fuks, H., 2013, March. Qualitative activity recognition of weight lifting exercises. In Proceedings of the 4th Augmented Human International Conference (pp. 116-123).

Machine Learning A-Z™ Hands-On Python & R In Data Science

Machine Learning in Healthcare Course with R

The task is to build a machine learning regression model will predict the number of absent hours. As Employee absenteeism is a major problem faced by every employer which eventually lead to the backlogs, piling of the work, delay in deploying the project and can have a major effect on company finances. The aim of this project is to find an issue…

A simple R program that implements a very basic Polynomial Regression on a small data set. Because these data set don't have liner relationship between independent variable and dependent variable. so if we use the liner model then well get very High error. so in these example w'll compare both the model and select which one is best.

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This repository contains the necessary scripts to derive off-target models through (1) A neural network framework based on Keras and Tensorflow (2)An autmomated machine learning framework based on AutoGluon

This repository is associated with propensity score analysis utilizing machine learning algorithms to examine the impact of health insurance on duration of hospital stay in the NYC SPARCS 2015 In-patient discharges dataset.

This is the repo hosting resources of the R User Group at the University of St. Gallen.

The goal of this project is to use different Machine Learning algorithms to try to predict the rating that an user will give to a movie. To achieve this, we will use the Machine Learning models and statistics that we have learnt during the Data Science course and we will finally choose the one that gets the minimum RMSE number. The dataset is al…

In this project I am interested in classifying if existing vessels have the option of using alternative fuels based on vessel specific features.

This was the Capstone project for my Masters degree. This project looked at data provided by Spotify in an effort to help determine which of 10 future tracks a listener would skip based on their listening history with 10 historical tracks in a session.

This project is to predict number of bikes rented in each bike stations with a temporal granularity of one hour.