Understand AutoML: Know what AutoML tools can do and where human input is still critical..Define Clear Goals: Set precise objectives to guide model selection and performance expectations..Clean Your Data: High-quality, well-labeled data ensures AutoML delivers accurate results..Feature Engineering Matters: Even with AutoML, smart feature choices improve model performance..Choose the Right Tool: Select AutoML platforms suited for your dataset size and problem type..Monitor Metrics: Track accuracy, precision, recall, and other metrics to avoid blind trust..Avoid Overfitting: Use cross-validation and regularization to keep models generalizable..Iterate and Compare: Test multiple AutoML runs and compare results for the best outcome..Human Oversight: Review models and predictions - automation cannot replace domain expertise..Read More Stories.Join our WhatsApp Channel to get the latest news, exclusives and videos on WhatsApp