Predictive-Maintenance-Practice

This is a Machine Learning Practice Case of Predictive Maintenance by Python with NASA's Turbofan Engine Degradation Simulation Data Set. The popular predictive and classification algorithms were implemented to build this project.

The codes of this repo was tested under the following environment:

• Windows 10 with Intel(R) i7-6700 CPU @ 3.40GHz, RAM 8G;
• Python 3.8 on Spyder IDE 4.0 (Anaconda3)

Packages used:

• Data Wrangling: NumPy 1.17 & pandas 0.25
• Visualization : Matplotlib 3.1.0 & seaborn 0.9.0 & Scikit-plot 0.37
• ML algorithm : scikit-learn 0.21.3 & xgboost 1.0