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Introduction

Automated Machine Learning (AutoML) has emerged as a transformative technology that simplifies the process of developing, training, and deploying machine learning models. By automating repetitive and complex tasks such as feature engineering, model selection, and hyperparameter tuning, AutoML allows organizations to leverage AI capabilities without requiring deep technical expertise.

According to Marketintelo, “The global Automated Machine Learning size was valued at approximately USD 2.3 billion in 2024 and is projected to reach USD 14.8 billion by 2032, growing at a compound annual growth rate (CAGR) of 26.5% during the forecast period 2024–2032.”

Read Full Research Study – “https://marketintelo.com/report/automated-machine-learning-market”

Drivers Behind the Rising Adoption of AutoML

One of the primary drivers of AutoML adoption is the growing need for data-driven decision-making across industries. As enterprises collect vast amounts of data, there is an increasing demand for tools that can extract insights quickly and accurately. AutoML bridges the gap by enabling non-experts…

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