From the course: Learning Amazon SageMaker AI
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Learning the steps to train a model - Amazon SageMaker Tutorial
From the course: Learning Amazon SageMaker AI
Learning the steps to train a model
- [Instructor] Training a machine learning model is just like being a personal coach for an athlete. Just like a coach guides an athlete through practice drills, adjust their techniques, and helps them improve over time, you'll be teaching your model how to perform based on the data you've prepared. Training is where your model learns to make predictions based on patterns in your dataset. Let's walk through the steps that ensure that your model is properly set up and ready to start learning effectively. First, split the training data. You need to evaluate how well your model performs on new unseen data. You do this by splitting the data into training and testing sets. Typically, 70 to 80% of your data is used for training, and 20 to 30% is set aside for testing. The algorithm is the engine that powers how your model learns from the data. So next, you want to choose the appropriate algorithm based on your task. Linear regression for continuous predictions or decision trees for…
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