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Added KerasJS and Lime (explainable ML)

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Muhammad Yaseen 2018-02-09 12:57:46 +05:00
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@ -487,6 +487,7 @@ Further resources:
* [figue](https://code.google.com/archive/p/figue) - K-means, fuzzy c-means and agglomerative clustering.
* [Gaussian Mixture Model](https://github.com/lukapopijac/gaussian-mixture-model) - Unsupervised machine learning with multivariate Gaussian mixture model.
* [Node-fann](https://github.com/rlidwka/node-fann) - FANN (Fast Artificial Neural Network Library) bindings for Node.js
* [Keras.js](https://github.com/transcranial/keras-js) - Run Keras models in the browser, with GPU support provided by WebGL 2.
* [Kmeans.js](https://github.com/emilbayes/kMeans.js) - Simple Javascript implementation of the k-means algorithm, for node.js and the browser.
* [LDA.js](https://github.com/primaryobjects/lda) - LDA topic modeling for Node.js
* [Learning.js](https://github.com/yandongliu/learningjs) - Javascript implementation of logistic regression/c4.5 decision tree
@ -1002,6 +1003,7 @@ be
* [visualize_ML](https://github.com/ayush1997/visualize_ML) - A python package for data exploration and data analysis.
* [scikit-plot](https://github.com/reiinakano/scikit-plot) - A visualization library for quick and easy generation of common plots in data analysis and machine learning.
* [Bowtie](https://github.com/jwkvam/bowtie) - A dashboard library for interactive visualizations using flask socketio and react.
* [lime](https://github.com/marcotcr/lime) - Lime is about explaining what machine learning classifiers (or models) are doing. It is able to explain any black box classifier, with two or more classes.
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#### Misc Scripts / iPython Notebooks / Codebases