Скачать или смотреть How to save and load model with joblib

When working with machine learning models, it's important to be able to save and load them, so that you can use them later without having to retrain them from scratch. In Python, there are libraries like joblib that make it easy to save and load models.

To save a model with joblib, you simply need to import the library and use the dump() function. You provide the function with the model you want to save and the name of the file where you want to save it. Once you've saved the model, you can load it back up later by using the load() function and providing it with the file name of the saved model.

It's important to note that joblib is not the only way of saving and loading models in Python. Other libraries such as pickle and dill can also be used. Additionally, models can also be saved in other formats such as .h5 or .pb which are more common for deep learning models.

In summary, saving and loading models is an important task in machine learning and joblib is one of the tools that makes it easy to do this in Python. It's a simple and convenient library that allows data scientists and developers to save and load models quickly and easily without having to retrain the model from scratch. However, it's also important to be aware of other options that are available.

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