Efficient Machine Learning Operations and Development

Efficient machine learning operations involve producing predictions in real-time or as a batch process while monitoring the quality of results. Tools like Selden, Waits, Bieses, and True Era aid in model operations. Feature engineering is crucial for converting raw data to features and ensuring data consistency between training and predictions without information leakage. ML feature stores like Tecton and labeling solutions like Scale and Snorkel help manage this process. Model development involves the mathematical modeling aspect at the top of the stack.