Overview
Model training is the process of teaching a machine learning model to make predictions or decisions based on data. It involves feeding the model data, adjusting its parameters, and evaluating its performance. Understanding model training is essential for building effective machine learning applications. This introduction will cover the basics of how models learn from data and the steps involved in the training process.
📚 Key Learning Objectives
- ✓ Define what model training is in machine learning.
- ✓ Identify the key steps in the model training process.
- ✓ Explain the importance of data in training a model.
- ✓ Describe how to evaluate a model's performance.
- ✓ Recognize common challenges faced during model training.
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