Análisis de la fuga de empleados de una empresa con implementación de un modelo de Machine Learning para acciones de fidelización.

Case study in Python that simulates a business scenario focused on adopting and selling a new coffee product from a different supplier. It utilizes decision tree algorithms, implemented using Jupyter notebooks and the sklearn library.

Data Science and Business Analytics Task-1 (Predict the percentage of an student based on the no. of study hours) Using simple linear regression model, forecasting the marks of a student based on the numbers of hours studied per day. Tool(s) Used - Python (Jupyter Notebook)

Task: Prediction using Supervised ML - Predicting the percentage of a student based on the no. of hours studied using a simple linear regression model. Dataset available at http://bit.ly/w-data. Tools used: Python, Jupyter Notebook

Communicating data using Python in a Jupyter notebook