Python programming assignments for Machine Learning by Prof. Andrew Ng in Coursera

👑 Multivariate exploratory data analysis in Python — PCA, CA, MCA, MFA, FAMD, GPA

Fast Best-Subset Selection Library

Decision Trees, Random Forest, Dynamic Time Warping, Naive Bayes, KNN, Linear Regression, Logistic Regression, Mixture Of Gaussian, Neural Network, PCA, SVD, Gaussian Naive Bayes, Fitting Data to Gaussian, K-Means

pca: A Python Package for Principal Component Analysis.

UnSupervised and Semi-Supervise Anomaly Detection / IsolationForest / KernelPCA Detection / ADOA / etc.

Front-end speech processing aims at extracting proper features from short- term segments of a speech utterance, known as frames. It is a pre-requisite step toward any pattern recognition problem employing speech or audio (e.g., music). Here, we are interesting in voice disorder classification. That is, to develop two-class classifiers, which can…

The foundational library of the Morpheus data science framework

Estudo e implementação dos principais algoritmos de Machine Learning em Jupyter Notebooks.

Robust PCA implementation and examples (Matlab)

Starter code of Prof. Andrew Ng's machine learning MOOC in R statistical language

Fast truncated singular value decompositions

This research project will illustrate the use of machine learning and deep learning for predictive analysis in industry 4.0.

Randomized Dimension Reduction Library

✍️ An intelligent system that takes a document and classifies different writing styles within the document using stylometric techniques.

Implementation of random Fourier features for kernel method, like support vector machine and Gaussian process model

Randomized Matrix Decompositions using R

An approach to document exploration using Machine Learning. Let's cluster similar research articles together to make it easier for health professionals and researchers to find relevant research articles.

A MATLAB toolbox for classifier: Version 1.0.7

Explorative multivariate statistics in Python