Heart Failure Prediction

Perform the Data analysis on the Heart Failure data set and draw insights.

Through this visualization easily understand what type of people have a high chance of getting Heart failure.

With the help of Various machine learning algorithms predict the accuracy of a chance of Heart Failure.

Accuracy -> 84%-87% | Tchnologies used - Python, Statistics, EDA, and classification ML Algorithms.

GitHub Link

Car Price Prediction

Performed Exploratory data analysis and found the predicted score (car price) based on the features data have in the data sets.

With the help of this visualization, we can easily predict the new car price.

Using two Machine Learning Algorithms, Regressor model Decision Tree Regressor and Random Forest Regressor.

Accuracy: 90% | Technologies used - Python, Statistics, EDA, and Regression ML Algorithms.

GitHub Link

Big Mart Sales Analysis

Data analysis on Big-mart sales over time and draw insights from the data

By this visualisation easily understand big mart sales views like losses, and profit in different cities.

With the help of this analysis can decide which products in which cities should more focus and increase sales and provide good customer service.

Technologies used - Python(Pandas, Numpy, Matplotlib, Seaborn).

GitHub Link

Credit Card Fraud Detection

Applied the features engineering on data set and also done the step backward feature selection.

Perform the Data analysis on the data set and draw insights(EDA).

Used classification Machine Learning Algorithms and find the accuracy scores(96%).

Technologies used: Python,sklearn,ML-classiification Algo.

GitHub Link