mle

There are 2 repositories under mle topic.

• kelvins / awesome-mlops

  :sunglasses: A curated list of awesome MLOps tools

  aiawesomedata-sciencemachine-learningmachine-learning-engineeringmlmlemlops
  Language:Python 3556
• frouros

  IFCA-Advanced-Computing / frouros

  Frouros: an open-source Python library for drift detection in machine learning systems.

  drift-detectionconcept-driftmachine-learningpythonstatisticsdata-driftmlopsmachine-learning-engineeringmachine-learning-operationsdataset-driftdataset-shiftmlechange-detectiondistribution-shift
  Language:Python 160

• ericsuh / dirichlet

  Dirichlet MLE python library

  dirichletmlepython
  Language:Python 108

• jkirkby3 / pymle

  Maximum Likelihood estimation and Simulation for Stochastic Differential Equations (Diffusions)

  diffusionsdemlemle-estimationsimulationmonte-carlomaximum-likelihoodstatisticsstochastic-differential-equationsfittingestimationpythonbrownianmaximum-likelihood-estimationmilsteinfitsdeslikelihoodait-sahalia
  Language:Python 40

• graalvm / mysql-mle-demos

  Demos for the MySQL Multi-Lingual Environment

  graalvmgraalvm-demosmlemysql
  16

• LongxingTan / Machine-learning-interview

  软件工程师、算法工程师、机器学习工程师、数据科学家实践与面试

  leetcodemachine-learningpythoninterviewsystem-designai-engineerai-internshipmachine-learning-algorithmssoftware-engineeringsoftware-engineer-interviewcoopml-systems-designdeep-learningalgorithmsnatural-language-processingrecommendation-systemmle
  15

• kyleclo / tensorflow-mle

  Some examples on computing MLEs using TensorFlow

  bfgsdescentgaussiangradientmixturemletensorflow
  Language:Python 14

• vineeths96 / TDOA-Localization

  In this repository, we deal with developing different estimators to localize Transvahan - the e-vehicle on IISc Campus using measurements from receivers at four different locations in IISc and implementing and evaluating the performance of the estimators that we have derived.

  tdoarangingestimationmultilaterationcrlbmlebluetriangulation
  Language:Python 12

• oracle-samples / mle-modules

  Documentation and interface declarations for MLE modules as provided in Oracle Database

  javascriptmleoracle-database
  10

• andreizolotarev / MLOps

  This repository contains examples of using various libraries/tools for MLOps.

  mlopsmlops-workshopmlemachine-learningmachinelearningengineeringmachine-learning-engineeringdata-sciencedockermlflowdvcredisailuigiairflowflask
  Language:Python 5

• kamath-abhijith / TDOA_Localisation

  TDOA Localisation using MLE and BLUE.

  localisationtdoamleblueestimationmontecarlo
  Language:Python 5

• paulnorthrop / chandwich

  Chandler-Bate Sandwich Loglikelihood Adjustment

  independence-loglikelihoodsandwichrobustmlestatistical-inferenceclustered-dataclusterscomposite-likelihood
  Language:R 4

• Fluorescence-Tools / fit2x

  Maximum likelihood fits for low photon count data - For active develeopment visit gitlab.peulen.xyz

  fluorescencemlemle-estimationlifetime-analysislifetimeflimsingle-molecule
  Language:C++ 3

• jonychoi / Alzheimer-Analysis-by-MLE

  Analysis about univariate and bivariate MLE between the diagnosis group of 'Alzheimer's Disease', 'Mild Cognitive Impariment', and 'Cognitive Normal'.

  alzheimer-diseasebrain-diseasesmedicalmleunivariate
  Language:Jupyter Notebook 3

• paulnorthrop / lax

  Loglikelihood Adjustment for Extreme Value Models

  loglikelihood-adjustmentregression-modellingextremesextreme-value-analysissandwichsandwich-estimatorevdpotrobustmleclustered-dataclustersindependence-loglikelihoodcomposite-likelihoodregressionextreme-value-statistics
  Language:R 3

• stxupengyu / maximum-likelihood-estimation

  介绍和举例（正态分布、泊松分布、伽马分布）展示了极大似然估计。This paper introduces and gives examples (normal distribution, Poisson distribution, gamma distribution) to show the MLE.

  mle-estimationmlemaximum-likelihood-estimation
  Language:Jupyter Notebook 3

• zhangyi-he / WFM-1L-DiffusApprox-MLE

  Estimation of natural selection and allele age from time series allele frequency data using a novel likelihood-based approach

  natural-selectionpopulation-geneticsallele-agehmmdiffusion-approximationwright-fisher-modelmleadnatime-series-data
  Language:R 3

• alanff15 / Non-Linear-Least-squares

  Non Linear Least squares solver and maximum Likelihood Estimation (MLE)

  maximum-likelihood-estimationmlenon-linear-least-squares
  Language:C++ 2

• biscalchin / dimention_estimation_By_Bisca

  IntrinsicDimEstimator is a Python module for estimating dataset intrinsic dimensionality, featuring multiple algorithms including CorrDim, NearNbDim, Packing Numbers, GMST, Eigenvalue Analysis, and MLE.

  data-analysisdata-sciencedimensionality-reductioninstrinsic-dimensionmachine-learningmlepcapythoncorrdimgmstintrinsic-dimensionalitynearnbdim
  Language:Python 2

• mahmutoezmen / Machine-Learning-Coursework

  Machine Learning 1 at TU Berlin

  machine-learningpython3bayesian-decision-theorymlexaisvmneural-networkspca
  Language:Jupyter Notebook 2
• maximum-likelihood-estimator

  Taabannn / maximum-likelihood-estimator

  This repository includes problems 9-10 & exercises 10-14 of Bertsekas probability book chapter9

  bertsekasexercises-solutionsjupyter-notebookmaximum-likelihood-estimationmleprobabilitypython3textbook-exercises
  Language:Jupyter Notebook 2

• williazo / tcensReg

  tcensReg is a package written to obtain maximum likelihood estimates from a truncated normal distribution with censoring.

  truncationcensregmlecensored-datatruncregnormal-estimationmaximum-likelihood-estimatescontrast-sensitivityvisual-qualitylimited-dependent-variable
  Language:R 2

• chen37058 / MLE-and-NaiveBayes

  极大似然估计法Python实现，朴素贝叶斯分类算法Python实现

  machine-learningmlenavebayes
  Language:Python 1

• chenzhaiyu / classifier

  Multi-spectral Classification with Maximum Likelihood Classifier

  classificationmlemultispectral
  Language:Python 1

• epiverse-trace / quickfit

  [Not published - under active development] Toolbox of model fitting helper functions

  distributionslikelihoodmler-packager
  Language:R 1

• gsantia / Gutenberg

  A tool for analyzing word counts of the Project Gutenberg text collection. Used in research reformulating the Zipf-Mandelbrot law.

  mlecomputationallinguisticstextnlpmap-reduce
  Language:Python 1

• hyzhak / mle

  Machine Learning: Maximum Likelihood Estimation (MLE)

  machine-learningmaximum-likelihood-estimationmlemapmaximum-a-posteriori-estimation
  Language:Jupyter Notebook 1

• kocmana / tw_mle_exercise5

  Technikum Wien - Machine Learning Exercise 5 - Deep Learning

  technikum-wienmle
  Language:Jupyter Notebook 1

• magerton / OrderedResponse.jl

  Ordered logit and probit models

  econometricslogit-modelprobitordered-responsemlejulia
  Language:Julia 1

• mahmoudrabie / apex-mle

  Thanks a lot for Daniel for his work. https://github.com/Dani3lSun/docker-db-apex-dev . I am trying here to add Oracle Database MLE.

  mleoracle-apex
  Language:Shell 1

• meenmo / UW-Madison_Math310

  Introduction to Mathematical Statistics II

  bayesianhypothesis-testingmathematical-statismlesampling
  Language:TeX 1

• Qianhongbo / Color-Classication-and-Recycling-Bin-Detection

  Project1: Color Classification and Recycling Bin Detection

  color-segmentationmleobject-detectionnaive-bayes
  Language:Python 1

• shill1729 / findistr

  distributions commonly used in finance

  estimationmlefinance
  Language:R 1

• TRI-MUPE / Useful_Reading

  Recommended reading material pertaining to MUPE and other multiplicative error regression techniques

  lolspingzmpemupemrlngrmlncobylagrgregressionregression-algorithmsnonlinear-optimizationnonlinear-regressionirlsleast-squareslevenberg-marquardtconstrained-optimizationmaximum-likelihood-estimationmle
  1

• ivanovsdesign / labs_stats_ml

  This repository contains 5 labs focusing on Statistics and Machine Learning concepts completed during Stats and ML course. Each lab is designed to provide practical experience and understanding of key topics in the field.

  knnlinear-regressionlogistic-regressionmathmethod-of-momentsmlepcaprobability-theorystatistics
  Language:Jupyter Notebook 0

• Rlvtick / Autocomplete-WebApp

  An Autocomplete WebApp to predict the next word or phrase by utilizing the MLE and simple N-gram probability model.

  mlenatural-language-processingngramsstreamlit-webapp
  Language:Python 0