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amazon-athena-user-guide

The open source version of the Amazon Athena documentation. To submit feedback & requests for changes, submit issues in this repository, or make proposed changes & submit a pull request.

back-propagation-algo-implementation

Back Propagation algorithm implemented from scratch using python. The program allows variable number of neurons and any activation function (provided the function and its derivative are defined in the code). To test if the algorithm is working, three cases are considered.

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expand-rank-with-string-subsequence-kernel

k-means-algo-implementation

Implemented k-Means algorithm in python from scratch. To demonstrate k-Means algorithm, three groups of data points (each group contains 40,000 points adding up to 1,20,000 points) were generated from a normal distribution with three different centers. At the end, a graph is generated which shows the working of the algorithm.

naive-bayes-implementation

Naive Bayes implemented from scratch in python. The algorithm is used to build a spam filter (using data from ). Training data consists of 70% of the data and the rest 30% of the data is treated as test data. Accuracy, precision and recall are then displayed for each category (spam and ham) as output.

perceptron-implementation

Perceptron implemented from scratch using python. A csv file consisting of some 2d points, some of them labelled 1 and others -1, is fed to the program and a hyperplane is plotted at the end, separating the two classes, demonstrating that the perceptron is working,

tower-of-hanoi-implementation