How Auto-ML is transforming AI: The Concept of ‘AI Creating AI’

AutoML automates several steps in the machine-learning process, including data preparation, model selection and hyperparameter tuning. It allows you to build AI models faster and better with minimal human intervention.

Traditional machine learning requires human intervention for feature engineering and hyperparameter tuning. Non-experts can build models faster and easier because autoML automates these processes.

AutoML helps data scientists automate repetitive tasks, but complex problem-solving, result interpretation, and unique solutions still require human skills.

Time savings, cost savings, better model accuracy, scalability, and democratization of AI, which make machine learning more accessible, are just a few of the benefits autoML brings.

AutoML is used for forecasting, decision-making, and operational efficiency. Healthcare, banking, retail, manufacturing and marketing.