Machine Learning

It is a subset of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention.

Machine learning model

A machine learning model is a program that can find patterns or make decisions from a previously unseen dataset. A machine learning model can perform such tasks by having it ‘trained’ with a large dataset. During training, the machine learning algorithm is optimized to find certain patterns or outputs from the dataset, depending on the task. The output of this process - often a computer program with specific rules and data structures - is called a machine learning model.

Machine learning model monitoring

The monitoring of machine learning models refers to the ways we track and understand our model performance in production from both a data science and operational perspective. Inadequate monitoring can lead to incorrect models left unchecked in production, stale models that stop adding business value, or subtle bugs in models that appear over time and never get caught.

Machine learning model retraining

The fundamental reason for model retraining is that the outside world that is being predicted keeps changing and consequently the underlying data changes, causing model drift. If comparing the training dataset and a similar set of new data shows a significant deviation, the existing model will no longer hold much value as it cannot make the same generalizations. In other words, the predictions the model makes are no longer as accurate as they were at the time of training.