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kk7nc / Text_Classification

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Text Classification Algorithms: A Survey
deep-learning random-forest text-classification recurrent-neural-networks naive-bayes-classifier dimensionality-reduction logistic-regression document-classification convolutional-neural-networks text-processing decision-trees boosting-algorithms support-vector-machines hierarchical-attention-networks nlp-machine-learning conditional-random-fields k-nearest-neighbours deep-belief-network rocchio-algorithm deep-neural-network
  • Updated Oct 16, 2020
  • Python

Madhu009 / Deep-math-machine-learning.ai

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A blog which talks about machine learning, deep learning algorithms and the Math. and Machine learning algorithms written from scratch.
machine-learning natural-language-processing deep-neural-networks tensorflow word2vec linear-regression q-learning neural-networks reinforcement-learning-algorithms sarsa logistic-regression gans support-vector-machines policy-iteration value-iteration gradient-descent-algorithm monte-carlo-methods temporal-differencing-learning general-adversarial-network
  • Updated Mar 15, 2019
  • Jupyter Notebook

gionanide / Speech_Signal_Processing_and_Classification

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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 discriminate between utterances of a subject suffering from say vocal fold paralysis and utterances of a healthy subject.The mathematical modeling of the speech production system in humans suggests that an all-pole system function is justified [1-3]. As a consequence, linear prediction coefficients (LPCs) constitute a first choice for modeling the magnitute of the short-term spectrum of speech. LPC-derived cepstral coefficients are guaranteed to discriminate between the system (e.g., vocal tract) contribution and that of the excitation. Taking into account the characteristics of the human ear, the mel-frequency cepstral coefficients (MFCCs) emerged as descriptive features of the speech spectral envelope. Similarly to MFCCs, the perceptual linear prediction coefficients (PLPs) could also be derived. The aforementioned sort of speaking tradi- tional features will be tested against agnostic-features extracted by convolu- tive neural networks (CNNs) (e.g., auto-encoders) [4]. The pattern recognition step will be based on Gaussian Mixture Model based classifiers,K-nearest neighbor classifiers, Bayes classifiers, as well as Deep Neural Networks. The Massachussets Eye and Ear Infirmary Dataset (MEEI-Dataset) [5] will be exploited. At the application level, a library for feature extraction and classification in Python will be developed. Credible publicly available resources will be 1used toward achieving our goal, such as KALDI. Comparisons will be made against [6-8].
nlp classifier natural-language-processing feature-extraction nltk gaussian-mixture-models support-vector-machines mfcc principal-component-analysis speech-processing linear-discriminant-analysis isomap spectral-clustering long-short-term-memory kernel-pca spectral-embedding locally-linear-embedding linear-prediction-coefficients speech-utterance
  • Updated Jul 15, 2020
  • Python

rishabhk108 / jensen

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A C++ toolkit for Convex Optimization (Logistic Loss, SVM, SVR, Least Squares etc.), Convex Optimization algorithms (LBFGS, TRON, SGD, AdsGrad, CG, Nesterov etc.) and Classifiers/Regressors (Logistic Regression, SVMs, Least Squares Regression etc.)
machine-learning machine-learning-algorithms sgd tron logistic-regression regularization gradient-descent support-vector-machines optimization-algorithms convex-optimization lbfgs-algorithm lbfgs jensen
  • Updated Oct 11, 2018
  • C++

zhaoyichanghong / machine_learing_algo_python

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implement the machine learning algorithms by python for studying
machine-learning deep-learning neural-network linear-regression collaborative-filtering gaussian-mixture-models gbdt logistic-regression tf-idf kmeans adaboost support-vector-machines decision-tree principal-component-analysis linear-discriminant-analysis spectral-clustering isolation-forest k-nearest-neighbor rbf-network gaussian-discriminant-analysis
  • Updated Oct 24, 2019
  • Python

OSSpk / Handwritten-Digits-Classification-Using-KNN-Multiclass_Perceptron-SVM

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🏆 A Comparative Study on Handwritten Digits Recognition using Classifiers like K-Nearest Neighbours (K-NN), Multiclass Perceptron/Artificial Neural Network (ANN) and Support Vector Machine (SVM) discussing the pros and cons of each algorithm and providing the comparison results in terms of accuracy and efficiecy of each algorithm.
svm machine-learning-algorithms mnist-dataset logistic-regression support-vector-machines knn artificial-neural-network handwritten-digit-recognition k-nearest-neighbours supervised-machine-learning support-vector-classifier perceptron-learning-algorithm sigmoid-function delta-rule mnist-classification-logistic comparative-study multiclass-perceptron learning-algorithms-comparison accuracy-analysis efficiency-analysis
  • Updated Sep 14, 2020
  • Python

sharmapratik88 / AIML-Projects

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Projects I completed as a part of Great Learning's PGP - Artificial Intelligence and Machine Learning
nlp data-science machine-learning statistics computer-vision random-forest data-visualization recommendation-system logistic-regression support-vector-machines decision-tree-classifier gradient-boosting-classifier knearest-neighbor-algorithm oversampling supervised-machine-learning unsupervised-machine-learning catboost ensemble-machine-learning machinelearningprojects datascienceproject
  • Updated Jun 24, 2020
  • Jupyter Notebook

hiroyuki-kasai / SparseGDLibrary

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MATLAB library of gradient descent algorithms for sparse modeling: Version 1.0.3
machine-learning big-data algorithms optimization machine-learning-algorithms solver lasso logistic-regression gradient-descent support-vector-machines admm proximal-algorithms proximal-operators sparse-regression optimization-algorithms matrix-completion elasticnet lasso-regression coordinate-descent sparse-linear-solver
  • Updated Nov 20, 2018
  • MATLAB

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