An ML Model is an implementation of machine learning algorithms that generates predictions, classifications, or recommendations based on input data. It learns from historical data and identifies patterns to make informed decisions.
Key Components:
- Data Input: The dataset used for training and testing the model.
- Algorithm: The mathematical method used to learn from data (e.g., decision trees, neural networks).
- Training Process: The phase where the model learns from data by adjusting its parameters.
- Output: The predictions or classifications generated by the model based on new input data.
ML models are widely used in various applications, including finance, healthcare and marketing. They help automate decision-making processes and improve operational efficiency.