For my Data Analytics subject I studied about car consumption habits depending on different factors collected in a survey made by Smartme Analytics.
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Updated
Dec 25, 2023 - R
For my Data Analytics subject I studied about car consumption habits depending on different factors collected in a survey made by Smartme Analytics.
The Problem Statement of this Project was to determine the likelihood of an employee to leave an organization.
Model predicts and detects the suicidal tendency of a person by runnning R script of ML algorithm.
Implementing different flavors of Classification and Regression Machine Learning Algorithms on different datasets in the US region.
Parkinson’s disease classification using speech signal features; comparison of various multiclass classification algorithms
Machine learning binary classification RStudio
Credit risk analysis using the LASSO, Random Forests and the SMOTE technique for balancing
R | Classification Project
Human resource has become one of the main concerns of managers in almost all types of businesses which include private companies, educational institutions and governmental organizations. Business Organizations are really interested to settle plans for correctly selecting proper employees. After hiring employees, managements become concerned abou…
This original code is the product of Travis Zalesky's Final Project in U. of AZ MS GIST class 601B - Remote Sensing. It is being provided publicly in the interest of transparity and repeatability.
Visualising 2Way Random Forest Interactions
Initial text mining exercise was performed on a dataset of Shark tank episodes with 495 entrepreneurs making their pitch to VCs. Used that to build multiple models (CART, Random Forest, Logistic Regression) to predict keywords which have an impact on striking a deal.
Student grade prediction using different machine learning models
A predictive analytics model for a Kaggle competition to predict the price of car using a dataset containing information on 40,000 used cars.
Using a variety of techniques, including descriptive analysis, machine learning models, and K-means clustering, to identify key customer segments.
Project in R developing a restaurant review classifier that makes predictions as positive or negative integrated with a Rest API in Node.js.
Random forest analysis of match statistics and team performances in five seasons of the English Premier League (EPL)
Classification of movie rankings
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