This repository demonstrates the scaling of the data using Scikit-learn's StandardScaler, MinMaxScaler, and RobustScaler.

Bank Customer Behaviour Prediction

Time Series Model

Exploratory Data Analysis for HR dataset

Cloud image generation with Python and OpneCV

Aircraft Engine Run-to-Failure Simulation

Used-Car_price prediction using XGBoost Regressor

In this project we will apply Recurrent Neural Network (LSTM) which is best suited for time-series and sequential problem, we will be creating a LSTM model, train it on data and make predictions to check its performance.

Stock price prediction is the process of forecasting future stock prices based on historical data and market indicators.

This advanced forecasting tool leverages Prophet, ARIMA, SARIMA, and LSTM models to predict daily sales for 32 pizzas and 64 ingredients. With Prophet achieving the lowest MAPE, it ensures accurate demand forecasts, optimized inventory, and efficient purchase planning, reducing waste, preventing stockouts, and enhancing supply chain efficiency.

Created machine learning models capable of classifying candidate exoplanets from a raw dataset.

Linear Regression+Decision Tree+Random Forest

This project is based on a classification algorithm i.e. Naive Bayes which is run on a mobile dataset consisting of 2000 rows and 15 columns. It is a multi-class problem where mobile phones are classified in accordance with their price range. There are four classes of price ranging from 0 to 3, 0 indicating cheaper mobiles phones and 3 represent…

Data Set: House Prices: Advanced Regression Techniques Feature Engineering with 80+ Features

Artificial Neural Network using Keras in python to identify customers who are likely to churn.