AI-900-3,4
Module : 3 Get Started with Machine Learning in Azure Machine learning drives today’s AI by turning data into insights for predictions and recommendations. Creating an ML solution requires key decisions that affect cost, speed, and quality. Using Microsoft Azure, the process follows six main steps: Define the Problem: Decide what to predict and how to measure success. Get the Data: Find and access reliable data sources. Prepare the Data: Clean, explore, and format the data for modeling. Train the Model: Choose algorithms and adjust parameters. Integrate the Model: Deploy it to generate predictions. Monitor the Model: Track performance and retrain as needed. Machine learning is an ongoing process. Models evolve as data changes. Step 1: Define the Problem The first step in building a machine learning (ML) solution is to define the problem. You need to clearly understand what you want the model to predict and how you will measure success. Key Considerations Model output: What result shoul...
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