What are the best practices for machine learning development?

What are the best practices for machine learning development?

Some best practices include data preprocessing, feature selection, model validation, and continuous monitoring.

Can you explain why data preprocessing is important?

Data preprocessing helps in cleaning and transforming raw data into a usable format, improving model accuracy.

What techniques can I use for feature selection?

Techniques include filter methods, wrapper methods, and embedded methods, each with its own advantages.

How often should I validate my model?

You should validate your model regularly, especially when new data is available or when the model's performance drops.