Docker for Machine Learning | How to use Docker and Dockerfile for Machine Learning Project?

Using Docker and Dockerfile for Machine Learning Project.

How to use Docker for machine learning? We’ll create a project that includes the following components:

A simple machine learning model: We’ll use a basic linear regression model using scikit-learn.

A Dockerfile: To define our Docker environment.

Data: A simple CSV file for training the model.

Typical workflow:

Data Loading and Preprocessing with Pandas:

Load data, clean, and preprocess using Pandas.

Model Training with Scikit-Learn:

Use Scikit-Learn to split the data, train a model, and evaluate its performance.

Model Saving with Joblib:
Serialize the model with Joblib for storage and reuse.

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