Linear Regression+Decision Tree+Random Forest

Bank Customer Behaviour Prediction

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

Feature transformation is a technique in machine learning that changes the way features are represented in order to improve the performance of machine learning algorithms. This can be done by transforming the features to a different scale, removing outliers, or creating new features from existing

Wrangled real estate data from multiple sources and file formats, brought it into a single consistent form and analysed the results.

Time Series Model

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

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…

This repository contains clustering techniques applied to minute weather data. It contains K-Means, Heirarchical Agglomerative clustering. I have applied various feature scaling techniques and explored the best one for our dataset

Forecasting time series data using ARIMA models. Used covariance matrix to find dependencies between stocks.

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.

Cloud image generation with Python and OpneCV

Predictive model that tells important factors(or features) affecting the demand for shared bikes

Telecommunication Company Churn Project

Final Cybersecurity ML project of Marc Mestre and Yana Veitsman for Data Mining and Machine Learning course at University of Valencia, Spring 2021

Aircraft Engine Run-to-Failure Simulation

Build a machine learning model to predict if a credit card application will get approved.

Exploratory Data Analysis for HR dataset

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