ML/DL code over-fitting model
Budget: $10 – $20 USD
Hi Experts,
I have a complete python ML model (end to end) with an accuracy of 100% on the test set. But when i make real life predictions, i get barely 40% accuracy.
Task:
1.) Identify and fix possible causes of over-fitting.
2.) Show proof that if we test the improved model on a live dataset, we'll see an accuracy of say 70% (on live data)
3.) Provide solution on Jupiter notebook or google.colab
I have a complete python ML model (end to end) with an accuracy of 100% on the test set. But when i make real life predictions, i get barely 40% accuracy.
Task:
1.) Identify and fix possible causes of over-fitting.
2.) Show proof that if we test the improved model on a live dataset, we'll see an accuracy of say 70% (on live data)
3.) Provide solution on Jupiter notebook or google.colab