Some Frameworks You Should Know About to Optimize Hyperparameter in Machine Learning Models

Optimizing hyperparameters is one of the key elements of the life cycle of machine learning solutions. Yet, the processes for hyperparameter optimization remain incredibly laborious and require considerable effort from data scientists. Lately, there a new generation of tools and platforms have emerged with the focus of streamlining the experience of optimizing hyperparameters. Building deep learning solutions in the real world is a process of constant experimentation and optimization. Differently from any other type of software application, deep learning applications don't have a linear lifecycle based on the fact that models need to constantly refined, optimized and tested.