Machine Learning Telecom Churn Model

HR Analytics Dataset

Bike Sharing in Washington D.C.

Explored data using data visualisation and exploratory data analysis. Used Logistic Regression to create a basic prediction model. Improved model using recursive feature elimination.

The given information of network connection, model predicts if connection has some intrusion or not. Binary classification for good and bad type of the connection further converting to multi-class classification and most prominent is feature importance analysis.

Linear Regression, how number of features affect outcome

King County House Sales

To identify the variables affecting house prices :Multiple Linear Regression in Python using statsmodels and RFE

A multiple linear regression model for the prediction of car prices.

CART, K-Means, Apriori, Adaboost, RFE; models using Anti-cancer peptides vs Human proteins

Computer Intelligence subject final project at UPC.

Supervised Learning for House Price Prediction with Support Vector Machine (LibSVM)

SVM classification, RFE feature selection

A Chinese automobile company Geely Auto aspires to enter the US market by setting up their manufacturing unit there and producing cars locally to give competition to their US and European counterparts. They have contracted an automobile consulting company to understand the factors on which the pricing of cars depends. Specifically, they want to …

An education company named X Education sells online courses to industry professionals. On any given day, many professionals who are interested in the courses land on their website and browse for courses. The company markets its courses on several websites and search engines like Google. Once these people land on the website, they might browse th…

Machine Learning Project

[Features extraction method] You can find the new version of CASTOR_KRFE at https://github.com/bioinfoUQAM/CASTOR_KRFE

Given features of car, training the model to predict the car price.