Added rslearn-py

[ItzRustam]

What's New

This PR adds rslearn-py to the docker-python image so it is available as part of the pre-installed Python package set.

Why?

rslearn-py is a lightweight machine learning library focused on keeping common ML workflows simple while providing useful functionality without adding unnecessary complexity or heavy dependencies. Including it in the image makes rslearn-py readily available to Python users and projects running in docker-python, while keeping the addition small and straightforward.

Links

source code : https://github.com/ItzRustam/rslearn-ML
web : https://rslearn-py.rslearnlib.workers.dev/

Usage

import numpy as np
from rslearn.linear_model import LinearRegression

# Training data
X = np.array([
    [1],
    [2],
    [3],
    [4],
    [5],
])

y = np.array([2, 4, 6, 8, 10])

# Train the model
model = LinearRegression()
model.fit(X, y, scale=True) # Auto Scales Data, saves time

# Make predictions
predictions = model.predict(np.array([[6], [7]])) # Scales new data also on saved StandardScaler configs.
print(predictions)

# Evaluations
evals = model.evaluate_model(y_pred=predictions, y_true=[12, 14])
print(evals) 
# This will return r2_score, rmse, mse, mae at once