Various projects dedicated to Machine Learning in a business perspective. Those projects are either made with Alteryx,Python or Excel directly.
They all rely on several steps:
In order to be able to perform machine learning, you need first to make sure your dataset is cleaned (no nulls, NaNs, outliers, ...).
After cleaning up the dataframe, it is required to analyze the data and understand them. You might also need to aggregate them and then see their correlation with one another.
There are different ways and aglorithms that can help predict an outcome (a turnover, churn rate, etc). Most of the techniques I used are:
- Linear Regression
- Logistic Regression
- Tree models (Random Forest and Decision Tree°
- Boosted models
- Cluster Analysis
- AB Testing
- Time series