In this project, I built a multiple linear regression model predicting the yearly amount spent of customers who bought clothes online using an app and a website using multiple and single features respectively using the F-Regression statistic for feature selection.

In this project, I built a simple and multiple linear regression model predicting the yearly amount spent of customers who bought clothes online using an app and a website using multiple and single features respectively. The dataset contained 500 rows and 8 columns of data.

I analysed a 1990’s Classic Hits dataset from kaggle with Python. This has 980 iconic 1990s singles performed by 536 different artists. Each track in the collection includes full Spotify audio feature data, allowing for in-depth analysis of musical properties like danceability, energy, key, loudness, mode, speechiness, acousticness, instrumentality, liveness, valence, tempo, and length.

In this project I analysed one of the trending datasets on Kaggle about weather type classification. The dataset is synthetically generated to mimic weather data for classification tasks. It contained 13,200 rows and 11 columns.

This shows an analysis of the electric power consumption in Tetouan, Morocco for the year 2017. The aim of this project was to majorly study the trend of power consumption in different zones in Tetouan while also considering the weather conditions.