AutoML: Automating the Machine Learning Pipeline
Keywords:
AutoML (Automated Machine Learning), Machine learning, Algorithms, Meta-learning, Neural Architecture Search (NAS)Abstract
Automation of the machine learning model-building process is the aim of the emerging field of "Automated Machine Learning, or AutoML". By automating as much of the repetitive, unproductive labour that arises when machine learning is used, autoML was developed to boost productivity and efficiency. Provide a thorough overview for machine learning researchers and practitioners, as well as a foundation for future advancements in AutoML. As a consequence, the method seems to be more effective in terms of operation time and memory use, while maintaining a similar level of output quality. However, based on the estimates we made; we can say that our technique has a great deal of potential for providing an excellent automated ML pipeline design solution. As a result, our next goal will be to make it as competitive as feasible.
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