In this project, a dataset containing credit card transactions is examined with the goal of training and testing a machine learning classifier models: K-Nearest Neighbors (KNN). The objective is to predict which transactions are likely to be fraudulent. After training the model, we will evaluate its …

In this project, we will leverage a dataset containing various features like beats per minute (bpm), energy, decibels (dB), acoustic characteristics, and more. The objective is to employ these features to make predictions for the target variable, which is the popularity of songs. Two regression …

Web scraping to extract top email senders In this project, I’m writing a Python script that will be used for extracting email data from a Gmail account, creating a Pandas DataFrame, and performing some data analysis and visualization. In the end we will be able to identify the email IDs of top …