Introduction to machine learning

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Machine Learning (ML) = the practice of making computers learn without explicitly programming insights into the algorithm.

Heuristic Approach = opposite of ML, mental shortcuts for solving problems in a quick way that delivers a result that is sufficient enough to be useful given time constraints.

Unsupervised Learning = work from scratch to find patterns and structures in the data.

Supervised Learning = Learning from examples i.e. labeled datasets.

Semi-supervised Learning = Only some data are labeled.

Measuring Performance=Accuracy, Precision, Recall, 

Categories of algorithms

- Clustering

- Classification

- Regression

- Dimensionality reduction

- Optimization

- Natural language processing

- Image processing

Clustering algorithms

- Average and distance

- K-Means algorithm

- K-Means 

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[MLJS][MLJS03]