Unravelling the Best Practices for DevOps Testing Strategy

Introduction to The Machine Learning Life CycleThe Machine Learning Life Cycle is the process used to build and deploy machine learning models. The stages of the machine learning life cycle are data collection, data preprocessing, model building, training, evaluation, and deployment. Defining the ProblemThe machine learning life cycle is a process that can help you develop successful machine learning models. Understanding what results or outcomes you hope to achieve from your system will help guide future decisions in the life cycle.  Model Building & Hyperparameter TuningModel building and hyperparameter tuning are two essential components of the machine learning life cycle.