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Practice and tutorial-style notebooks covering wide variety of machine learning techniques

numpy statistics pandas matplotlib regression scikit-learn classification principal-component-analysis clustering decision-trees random-forest dimensionality-reduction neural-network deep-learning artificial-intelligence data-science machine-learning k-nearest-neighbours naive-bayesImplicitly-restarted Lanczos methods for fast truncated singular value decomposition of sparse and dense matrices (also referred to as partial SVD). IRLBA stands for Augmented, Implicitly Restarted Lanczos Bidiagonalization Algorithm. The package provides the following functions (see help on each for details and examples).Help documentation for each function includes extensive documentation and examples. Also see the package vignette, vignette("irlba", package="irlba").

svd pca principal-component-analysis singular-value-decompositionPrincipal component analysis in Ruby. Uses GSL for calculations. PCA can be used to map data to a lower dimensional space while minimizing information loss. It's useful for data visualization, where you're limited to 2-D and 3-D plots.

pca principal-component-analysis rubymlWIP Machine learning library, written in J. Various algorithm implementations, including MLPClassifiers, MLPRegressors, Mixture Models, K-Means, KNN, RBF-Network, Self-organizing Maps. Models can be serialized to text files, with a mixture of text and binary packing. The size of the serialized file depends on the size of the model, but will probably range from 10 MB and upwards for NN models (including convnets and rec-nets).

machine-learning convolutional-neural-networks j deep-learning gaussian-mixture-models gaussian-processes self-organizing-map principal-component-analysis k-means hierarchical-clustering lstm ensemble-learning learning rbm restricted-boltzmann-machines multilayer-perceptron-network knn-classifier clusteringThis package provides various tools for classification, e.g., image classification, face recogntion, and related applicaitons. Run run_me_first for path configurations.

face-recognition classification classification-algorithims covariance-matrix sparse-coding linear-regression linear-discriminant-analysis principal-component-analysis symmetric-positive-definite spd subspace manifold matlab-toolbox dictionary-learning manifold-optimization support-vector-machines src eigenfaces pcaPersonal code for principal component analysis and diffusion map examples. Specifically made to test the idea on some well-known types of data, but it wouldn't take much to modify the source for use with whatever data set or distance metric you desire. A library is compiled with the classes needed for the main program and the main program links to that. The main program requires json-fortran. LAPACK is required for the library to calculate the eigenvectors and eigenvalues of various matrices.

data-science dimensionality-reduction principal-component-analysis kernel-trickWe propose a user-friendly ChIP-seq and RNA-seq software suite for the interactive visualization and analysis of genomic data, including integrated features to support differential expression analysis, interactive heatmap production, principal component analysis, gene ontology analysis, and dynamic network visualization. MicroScope is financially supported by the United States Department of Defense (DoD) through the National Defense Science and Engineering Graduate Fellowship (NDSEG) Program. This research was conducted with Government support under and awarded by DoD, Army Research Office (ARO), National Defense Science and Engineering Graduate (NDSEG) Fellowship, 32 CFR 168a.

chip-seq rna-seq heatmap gene-ontology principal-component-analysis differential-expression network-analysis gene-expression computational-biology r-programming statistical-analysisGod gave you one face and you went on to get a peek into what the future holds for you. On a technical note, the application uses the robust techniques of Principal component analysis and eigenfaces to decrypt your future.

eigenfaces principal-component-analysis flask deep-learning machine-learningThis is the R version assignments of the online machine learning course (MOOC) on Coursera website by Prof. Andrew Ng. This repository provides the starter code to solve the assignment in R statistical software; the completed assignments are also available beside each exercise file.

machine-learning learning-curve pca linear-regression gradient-descent svm principal-component-analysis clustering neural-network k-means recommender-system classification regularization anomalydetection ghEsse repositório foi criado com a intenção de difundir o ensino de Machine Learning em português. Os algoritmos aqui implementados não são otimizados e foram implementados visando o fácil entendimento. Portanto, não devem ser utilizados para fins de pesquisa ou outros fins além dos especificados.

machine-learning machine-learning-algorithms adaboost decision-trees kmeans knn linear-discriminant-analysis principal-component-analysis naive-bayes regression linear-regression neural-network redes-neurais-artificiais multilinear-regression polynomial-regression feature-selection
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