ML_from_scratch

Machine learning algorithms from scratch. Some of the algorithms are unfinished and the code structure is likely to change.

Finshed algorithms:

KMeans clustering: Partitions n observations into k clusters based on relative distance to cluster centers.
KNN (k-nearest neighbours): Test points are classified by majority vote of the nearby training points. It is recommmended that k is an odd number.
DBSCAN (Density-based spatial clustering of applications with noise): Groups together points that are closely packed together (points with many nearby neighbours), marking any outliers points that lie alone in low-density regions.
Logistic regression: Used to classify binary variables.

Unfinished:

Name		Name	Last commit message	Last commit date
Latest commit History 24 Commits
DBSCAN.ipynb		DBSCAN.ipynb
KNN.ipynb		KNN.ipynb
NN.ipynb		NN.ipynb
README.md		README.md
kmeans.ipynb		kmeans.ipynb
logistic_regression.ipynb		logistic_regression.ipynb

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