ml-lab-codes

An educational Python library that provides instant access to complete source codes for Machine Learning Laboratory experiments (Experiments 1a to 5b).

Designed for students, educators, and developers to easily view, inspect, and copy verified lab experiment programs directly in the Python shell, terminal, or Jupyter/Colab notebooks without having to execute the scripts or download datasets.

Features

• Zero-Dependency Code Inspection: Display verified machine learning lab programs without downloading datasets or running heavy training loops.
• Single Function API: Use show_code(program_number) to print the full source code for any program (1 to 5).
• All Experiments Covered: Includes all sub-experiments (e.g. 1a & 1b, 3a & 3b, 4a & 4b, 5a & 5b) mapped into 5 self-contained programs.

Installation

Install via pip:

pip install ml-lab-codes

If you plan to run and execute the machine learning models locally, you can also install the optional ML dependencies:

pip install "ml-lab-codes[ml]"

Usage

Display Program Code

import ml_lab_codes

# Print the complete code for Experiment 1 (1a & 1b)
ml_lab_codes.show_code(1)

You can also import show_code directly:

from ml_lab_codes import show_code

# Display Experiment 3 (ID3 & CART Decision Trees)
show_code(3)

List All Available Programs

import ml_lab_codes

ml_lab_codes.list_programs()

Programme Mapping

Error Handling

If an invalid or out-of-range program number is passed:

from ml_lab_codes import show_code

try:
    show_code(6)
except ValueError as e:
    print(e)
    # Output: Invalid program number '6'. Please choose a number from 1 to 5.

License

MIT License. See LICENSE for details.