Predictive Equipment Failures - SP

Inspiration

To better identify the failures

What it does

It predicts the failures based on sensor data

How we built it

We used ML algorithms. We performed exploratory data analysis and built classifier models

Challenges we ran into

The complexity of data and there was no description on what each sensor data represents

Accomplishments that we're proud of

That we were able to classify the data with a high F1 score

What we learned

We learned that real-time data is not that easy to work with. Extensive data cleaning and preprocessing is required to train a model

What's next for Predictive Equipment Failures - SP

Feature engineering can be done

Built With

• numpy
• pandas
• python
• scikit-learn