From the course: Develop ML Models with Python and T-SQL
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Model development
From the course: Develop ML Models with Python and T-SQL
Model development
- [Narrator] As an overview, let's discuss model development and training, how the model can be used to make a prediction, and lastly, the various scenarios that we can utilize machine learning models. For starters, the model is developed by collecting and loading data. We then utilize this data to train the model using the fit() method, and then afterwards we evaluate the model using various metrics. If we're satisfied, we can then save the model. If not, the cycle continues to repeat by feeding it more data, training it, and then evaluating it. Once the model is trained, it can then be saved and utilized for future predictions. To be able to use a trained model, essentially, we would utilize the load() method and then we would use the predict() method to be able to make a call and pass it in specific data or a feature, and then be able to get a prediction as a result. Some of the various scenarios that can be utilized for the machine learning are classification and categorization…
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