Training a Machine Learning Model

In this lesson, we'll cover the process of training an ML model.

Training process

Regardless of the chosen task, the ML process consists of the following fundamental steps:

1. Data collection: The first step is to collect and preprocess the relevant data required for the model. This includes data cleaning, normalization, feature extraction, and data labeling.

2. Model selection: The second step is to select an appropriate ML algorithm that can learn from the data and make predictions.

3. Model training: The third step is to train the selected ML algorithm on the preprocessed data. During training, the algorithm learns from the data and adjusts its parameters to minimize the error between the predicted output and the actual output.

4. Model evaluation: The fourth step is to evaluate the performance of the trained model using a separate set of data called the validation set. ...