🤔 That's what I know :

Data Collect and Storage: SQL, MySQL and PostgreSQL.

Data Processing and Analysis: Python.

Development: Git, Scrum and Linux.

Data Visualization: Tableau and Power BI.

Machine Learning Modeling: Classification, Regression and Clustering.

Machine Learning Deployment: Heroku and AWS Cloud.

🏡 How to reach me:

My strategy to solve this challenge was test machine learning models to forecast sales for the next 6 weeks and decide which will bring the best result for the company. After the modelling, the delivered solution was a telegram bot that receives the store number and returns the forescast for the next weeks.

With a classic churn prediction problem with imbalanced data, I train a machine learning algorithm to predict churn clients and create a strategy to bring back the clients. The solution was created with a help of the 0-1 Knapsack Problem and a possible investment. After that, the solution was a web app using streamlit that can create simulations using the knapsack-problem and the model, showing churn reduction, ROI and clients returned.

“Be passionate and bold. Always keep learning. You stop doing useful things if you don't learn.”

Satya Nadella