Detecting a Rock or a Mine (using KNN) :

Sonar (sound navigation ranging) is a technique that uses sound propagation (usually underwater, as in submarine navigation) to navigate, communicate with or detect objects on or under the surface of the water, such as other vessels.

The data set contains the response metrics for 60 separate sonar frequencies sent out against a known mine field (and known rocks). These frequencies are then labeled with the known object they were beaming the sound at (either a rock or a mine).






Our main goal is to create a machine learning model capable of detecting the difference between a rock or a mine based on the response of the 60 separate sonar frequencies.

Presence Of heart Disease (using Logistic Regression) :
A Classification Model that can predict whether or not a person has presence of heart disease based on physical features of that person (age,sex, cholesterol, etc...)


This database contains 14 physical attributes based on physical testing of a patient. Blood samples are taken and the patient also conducts a brief exercise test. The "goal" field refers to the presence of heart disease in the patient. It is integer (0 for no presence, 1 for presence).

To confirm 100% if a patient has heart disease can be quite an invasive process, so if we can create a model that accurately predicts the likelihood of heart disease, we can help avoid expensive and invasive procedures.

Prediction Of house price (using Linear Regression) :
The Ames Housing dataset is a popular resource for exploring regression and predictive modeling.

It contains detailed information about 2,930 properties in Ames, Iowa, with 82 features describing various aspects of the houses. These features include:

Lot characteristics: Size, shape, and frontage.

Building details: Year built, style, and type of dwelling.

Neighborhood information: Proximity to amenities and physical location within Ames.

Quality ratings: Overall material quality, condition, and specific evaluations like basement or exterior quality.

Sale details: Price, zoning classification, and type of sale.

Data Analysis of Fandango website (Cinema Website)
If you are planning on going out to see a movie, how well can you trust online reviews and ratings?
*Especially* if the same company showing the rating *also* makes money by selling movie tickets.
Do they have a bias towards rating movies higher than they should be rated?

Our main goal is to explore whether or not Fandango artificially displays higher ratings than warranted to boost ticket sales.