Feature Store for Machine Learning

Chapter 1: An Overview of the Machine Learning Life Cycle

Machine learning (ML) is a subfield of computer science that involves studying and exploring computer algorithms that can learn the structure of data using statistical analysis. The dataset that's used for learning is called training data. The output of training is called a model, which can then be used to run predictions against a new dataset that the model hasn't seen before. There are two broad categories of machine learning: supervised learning and unsupervised learning. In supervised learning, the training dataset is labeled (the dataset will have a target column). The algorithm intends to learn how to predict the target column based on other columns (features) in the dataset. Predicting ...