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What is AutoML in Machine Learning?

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  • Last Updated : 27 Dec, 2019

Machine Learning is the most popular technology in current times!!! It is currently utilized in almost every field imaginable which has pushed its importance infinitely. But what about those who don’t know Machine Learning as well? That’s where Automated machine learning or AutoML comes in!

Automated machine learning (AutoML) basically involves automating the end-to-end process of applying machine learning to real-world problems that are actually relevant in the industry. In recent years, it has been noticed as well as proven time and time again that ML or machine learning is the key to the future. It is understandable that this is an up and coming technology that allows for various directions of research, analysis, and implementation.

However, the use of this vast and powerful technology is limited to the number of data scientists and machine learning enthusiasts and researchers, which are low in number and slowly rising. To bridge this gap the theory or concept of Automated Machine Learning came into the picture. A data scientist has to apply the appropriate data pre-processing, parameter engineering, parameter extraction, and parameter selection methods that make the dataset ready for inference and hence for data analysis. Following those pre-processing steps, an algorithm must be appropriately selected and hyper-parameter optimization must be performed to maximize the predictive performance of their final machine learning model. As many of these steps can only be performed by ML experts, AutoML was proposed as an artificial intelligence-based solution to the challenge of easily applying machine learning without much expertise. Google one of the leading tech-giants has released the Cloud AutoML for making custom machine learning models based on business to business.

It is important that this field of Automated machine learning is researched on and more communities are included as it is an area of utmost importance and a field of untapped potential. One such open-source project is AutoKeras which performs or is used for neural architecture search. AutoKeras is an open-source software library that is used for automated machine learning (AutoML). It is developed by DATA Lab at Texas A&M University and community contributors. AutoKeras helps in fulfilling the ultimate goal of AutoML, which is to provide freely available deep learning tools to domain experts who only have a basic machine learning or data science background.

Thus we can conclude from this article that AutoML maybe a new field, however, it has boundless opportunities and may even be a completely new field of machine learning in the future.

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