Scikit-tutorial

This Repository contains major statistical implementation of statistical machine learning algorithms with a pinch of theory here and there!

You can find a printable webpage of each tutorial below:

An additional tutorial of Numpy-stack can be found here at:

Name		Name	Last commit message	Last commit date
Latest commit History 9 Commits
LICENSE		LICENSE
README.md		README.md
SMSSpamCollection		SMSSpamCollection
Scikit- Tutorial Logistic Regression.ipynb		Scikit- Tutorial Logistic Regression.ipynb
Scikit-Tutorial K- Means.ipynb		Scikit-Tutorial K- Means.ipynb
Scikit-Tutorial PCA.ipynb		Scikit-Tutorial PCA.ipynb
Scikit-Tutorial-SVM.ipynb		Scikit-Tutorial-SVM.ipynb
Scikit-tutorial Artificial Neural Networks.ipynb		Scikit-tutorial Artificial Neural Networks.ipynb
Scikit-tutorial Decision Trees.ipynb		Scikit-tutorial Decision Trees.ipynb
Scikit-tutorial- Feature Extraction .ipynb		Scikit-tutorial- Feature Extraction .ipynb
Scikit-tutorial-Linear Regression.ipynb		Scikit-tutorial-Linear Regression.ipynb
requirements.txt		requirements.txt