Practical Machine Learning on Databricks
Machine learning teams today must build scalable, production-ready workflows that move seamlessly from experimentation to deployment and monitoring. This course provides a practical introduction to machine learning on Databricks, helping professionals leverage modern tools such as AutoML, MLflow, Feature Store, and serverless deployment to streamline ML operations and accelerate business outcomes. Through hands-on examples and real-world scenarios, you will learn how to create baseline models, manage feature engineering workflows, automate ML pipelines, and deploy models efficiently using Dat
Skills you'll learn
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