How to fine-tune the Machine Learning Models?
In your practical experience, which techniques worked better to improve the accuracy of your machine learning model?
You are welcome to share your experience in the comments:
Some of the suggested techniques:
1. Adding more data
2. Data Cleaning
3. Feature Engineering
4. Algorithm tuning
5. Ensemble methods
6. Handling Imbalanced Data
7. Tune Hyperparameters
8. Regularization & Dimensionality Reduction
You can see the submitted comments in the original link: