In this data science and machine learning project, we classify sports personalities. We restrict classification to only 5 people. In this model firstly we collected images of the athletes from the internet and then cropped all the face detected in images using OpenCV. Then we Wavelets transformed the images to extract the key feature of the faces. Then we created a training set to train the data. We tried many algorithms but chose SVM as it was giving the best results.

This Model/WebApp predicts real estate price in Bangalore. Many times we have come across websites like “Magicbricks.com” where they sell and estimate the price of the property in any part of the country, so this model is also inspired by the concept of predicting property prices based on the area, bedrooms, bathrooms and location. Firstly I built the model using sklearn and machine learning algorithm using Bangalore home prices dataset from kaggle.