breezeml 0.1.2

🌬️ BreezeML 🔥✨ — A beginner-friendly machine learning library built on scikit-learn.

🌬️ BreezeML 🔥✨

If you can load a CSV, you can train a model.
Beginner-friendly machine learning on top of scikit-learn — zero boilerplate.

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🧩 What is BreezeML?

• One line to train a model (fit) and one line to predict (predict).
• Auto mode chooses classification vs regression.
• Built-in datasets: Iris, Wine, Breast Cancer, Diabetes.
• Save/Load models easily.
• Kid-friendly API with sensible defaults.

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📦 Install

pip install breezeml

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⏱️ 60-Second Quickstart

from breezeml import datasets, fit, predict, creator

print(creator())  # Easter Egg 🔥✨
df = datasets.iris()
model = fit(df, "species")
print(predict(model, df.drop(columns=["species"]))[:5])

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🔮 Auto-Magic Mode

from breezeml import auto, datasets

df = datasets.diabetes()
model, report = auto(df, "target")
print(report)  # r2, mae, rmse

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🧮 Built-in Classifiers (v0.1.2)

Use popular classifiers in one line:

from breezeml import classifiers, datasets
df = datasets.iris()
model, report = classifiers.gaussian_nb(df, "species")
print(report)  # {'accuracy': ..., 'f1': ...}

Available: classifiers.logistic, classifiers.svm, classifiers.linear_svm, classifiers.gaussian_nb, classifiers.multinomial_nb, classifiers.decision_tree, classifiers.random_forest

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🧊 Clustering (v0.1.2)

Unsupervised learning in one line:

from breezeml import clustering, datasets
df = datasets.wine()
res = clustering.kmeans(df.drop(columns=["class"]), n_clusters=3)
print(res["silhouette"], res["labels"][:10])

Available: clustering.kmeans, clustering.agglomerative, clustering.dbscan

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📄 Use Your Own CSV

from breezeml import from_csv
model, report = from_csv("data.csv", target="price")
print(report)

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💾 Save & Load

from breezeml import save, load, datasets, fit
df = datasets.iris()
model = fit(df, "species")
save(model, "iris_model.joblib")
loaded = load("iris_model.joblib")

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🛠️ Troubleshooting

• “Module not found”: pip install breezeml
• “Columns do not match”: new data must have same feature names as training
• “Version issue”: pip install --upgrade scikit-learn pandas numpy

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🗺️ Project Status

• Current: v0.1.2
• Roadmap: quick_tune(), explain(), plots, more datasets

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🤝 Contribute

PRs welcome! See CHANGELOG and examples.

📜 License

MIT © 2025 Akash Anipakalu Giridhar 🔥✨