mlhelper-exam 1.0.0

CLI tool that prints complete ML lab programs to stdout

mlhelper — ML Lab Programs CLI

A Python package that prints complete Machine Learning lab programs to stdout via a simple terminal command.

Installation

From wheel (offline)

pip install mlhelper_exam-1.0.0-py3-none-any.whl

From PyPI (online)

pip install mlhelper-exam

From source

cd exam/
pip install .

---

Usage

List all programs

mlhelper

+------------------------------------------+
|       mlhelper - ML Lab Programs         |
+------------------------------------------+

   1.  EDA - Outlier Counts (California)
   2.  EDA - Correlation Heatmap (California)
   3.  PCA on Iris Dataset
   4.  Find-S Algorithm
   5.  KNN Classification from Scratch
   6.  Locally Weighted Regression
   7.  Program 7 (Not Available)
   8.  Decision Tree (Breast Cancer)
   9.  Naive Bayes (Olivetti Faces)
  10.  K-Means Clustering (Breast Cancer)

Usage: mlhelper <number>

Print a specific program

mlhelper 1        # prints Program 1
mlhelper 4        # prints Program 4
mlhelper 10       # prints Program 10

Save a program to a file

mlhelper 3 > pca_iris.py
python pca_iris.py

---

Program Mapping

Number	Algorithm	Source File / Dataset
1	EDA - Outlier Counts	California Housing
2	EDA - Correlation & Deep Dive	California Housing
3	PCA on Iris	Iris
4	Find-S Algorithm	training_data.csv
5	KNN from Scratch (1-D)	Synthetic 1-D Data
6	Locally Weighted Regression	Synthetic LWR Data
7	Not Available	-
8	Decision Tree Classifier	Breast Cancer
9	Naive Bayes Classifier	Olivetti Faces
10	K-Means Clustering	Breast Cancer

---

Build a wheel

Build the wheel using standard pip tools:

pip wheel . --no-deps -w dist

The .whl file is created in the dist/ folder.

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Project Structure

exam/
├── pyproject.toml
├── requirements.txt
├── README.md
└── mlhelper/
    ├── __init__.py
    ├── cli.py
    └── programs/
        ├── __init__.py
        ├── p01_eda_outliers.py
        ├── p02_eda_correlation.py
        ├── p03_pca_iris.py
        ├── p04_find_s.py
        ├── p05_knn_scratch.py
        ├── p06_lwr.py
        ├── p07_not_available.py
        ├── p08_decision_tree.py
        ├── p09_naive_bayes.py
        └── p10_kmeans.py