Improving a Machine Learning Model

Classification Model (End to End Classification of Heart Disease - UCI Data Set)

Regression - Bulldozer Sales Price - Kaggle Competition

Goal Using the data collected from existing customers, build a model that will help the marketing team identify potential customers who are relatively more likely to subscribe term deposit and thus increase their hit ratio

Goal is to predict the concrete compressive strength using collected data

Flight-Price-Prediction. With this end to end Project you can able to get FliGht Ticket Fare from your place.

Hyper Parameter Techniques

Telecom Churn Case Study

I have built a Model using the Random Forest Regressor of California Housing Prices Dataset to predict the price of the Houses in California.

I have built a Model using Random Forest Regressor of California Housing Prices Dataset to predict the price of the Houses in California.

A Python Machine Learning Project designed to predict Halloween Candy sales for a company based on historical data

A Python Machine Learning project to classify the Iris Dataset

Practice and become familiar with regressions

6th Project for the Post Graduate Programme in Data Science and Business Analytics at the University of Texas at Austin - Model Tuning (GridSearchCV & RandomizedSearchCV)

classifying a patient has a heart disease or not

Buliding a ML model for predicting the selling price of a car

The repository contains the California House Prices Prediction Project implemented with Machine Learning. The app was deployed on the Flask server, implemented End-to-End by developing a front end to consume the Machine Learning model, and deployed in Azure, Google Cloud Platform, and Heroku. Refer to README.md for demo and application link

determining flight prices based on different parameters

Hyperparameter tuning using gridsearchCV and randomizedsearchCV