AutoML or Automated Machine Learning as the term suggests refers to streamlining the creation of machine learning models through automated ways. The traditional machine learning model development process requires a high level of expertise as AI professionals must be well acquainted with various data science techniques. However, AutoML helps to automate several development steps and make it accessible to a wider range of users.
AutoML technology has been rapidly gaining traction as the AutoML market is expected to reach around $6.4 billion by 2028 growing at a CAGR of 44.6% (as predicted by Markets and Markets).
This increase in AutoML platforms can be directly attributed to several reasons such as the increased demand for ML tools. Businesses across various industries understand the importance of ML models and want effective tools to streamline their operations. Another reason for the growth of AutoML is the democratization of AI because of which even non-experts can leverage ML for tasks like fraud detection, customer churn prediction, product recommendation, etc.
Well, the applications of ML are many and so is that of AutoML. So, everyone looking to advance in their AI career must be aware of AutoML, its advantages, types, and uses.
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