DTHB3D RegThis package performs 3D non-rigid image registration for medical and synthetic images using truncated hierarchical B-splines (THB-Splines)
Stars: ✭ 17 (-60.47%)
sgdAn R package for large scale estimation with stochastic gradient descent
Stars: ✭ 55 (+27.91%)
Machine-learningThis repository will contain all the stuffs required for beginners in ML and DL do follow and star this repo for regular updates
Stars: ✭ 27 (-37.21%)
gpDifferentiable Gaussian Process implementation for PyTorch
Stars: ✭ 18 (-58.14%)
ICC-2019-WC-predictionPredicting the winner of 2019 cricket world cup using random forest algorithm
Stars: ✭ 41 (-4.65%)
combining3DmorphablemodelsProject Page of Combining 3D Morphable Models: A Large scale Face-and-Head Model - [CVPR 2019]
Stars: ✭ 80 (+86.05%)
TFDeepSurvCOX Proportional risk model and survival analysis implemented by tensorflow.
Stars: ✭ 75 (+74.42%)
bioc 2020 tidytranscriptomicsWorkshop on tidytranscriptomics: Performing tidy transcriptomics analyses with tidybulk, tidyverse and tidyheatmap
Stars: ✭ 25 (-41.86%)
probai-2019Materials of the Nordic Probabilistic AI School 2019.
Stars: ✭ 127 (+195.35%)
regression-wasmTesting doing basic regression with web assembly
Stars: ✭ 32 (-25.58%)
deepvismachine learning algorithms in Swift
Stars: ✭ 54 (+25.58%)
ml-modelsMachine Learning Procedures and Functions for Neo4j
Stars: ✭ 63 (+46.51%)
Machine-Learning🌎 I created this repository for educational purposes. It will host a number of projects as part of the process .
Stars: ✭ 38 (-11.63%)
mcmcA C++ library of Markov Chain Monte Carlo (MCMC) methods
Stars: ✭ 108 (+151.16%)
approxposteriorA Python package for approximate Bayesian inference and optimization using Gaussian processes
Stars: ✭ 36 (-16.28%)
GPBoostCombining tree-boosting with Gaussian process and mixed effects models
Stars: ✭ 360 (+737.21%)
LogDensityProblems.jlA common framework for implementing and using log densities for inference.
Stars: ✭ 26 (-39.53%)
bnpBayesian nonparametric models for python
Stars: ✭ 17 (-60.47%)
theedhum-nandrumA sentiment classifier on mixed language (and mixed script) reviews in Tamil, Malayalam and English
Stars: ✭ 16 (-62.79%)
AIML-ProjectsProjects I completed as a part of Great Learning's PGP - Artificial Intelligence and Machine Learning
Stars: ✭ 85 (+97.67%)
lin-im2imLinear image-to-image translation
Stars: ✭ 39 (-9.3%)
GPflow-Slimcustomized GPflow with simple Tensorflow API
Stars: ✭ 17 (-60.47%)
playing with vaeComparing FC VAE / FCN VAE / PCA / UMAP on MNIST / FMNIST
Stars: ✭ 53 (+23.26%)
DynamicHMCExamples.jlExamples for Bayesian inference using DynamicHMC.jl and related packages.
Stars: ✭ 33 (-23.26%)
polatoryFast, memory-efficient 3D spline interpolation and global kriging, via RBF (radial basis function) interpolation.
Stars: ✭ 82 (+90.7%)
TemporalGPs.jlFast inference for Gaussian processes in problems involving time. Partly built on results from https://proceedings.mlr.press/v161/tebbutt21a.html
Stars: ✭ 89 (+106.98%)
TotalLeastSquares.jlSolve many kinds of least-squares and matrix-recovery problems
Stars: ✭ 23 (-46.51%)
stantargetsReproducible Bayesian data analysis pipelines with targets and cmdstanr
Stars: ✭ 31 (-27.91%)
info-retrievalInformation Retrieval in High Dimensional Data (class deliverables)
Stars: ✭ 33 (-23.26%)
PointProjectorA simple Cinema 4D plugin that non-destructively projects the points of a spline or polygon object on geometry.
Stars: ✭ 20 (-53.49%)
ArviZ.jlExploratory analysis of Bayesian models with Julia
Stars: ✭ 67 (+55.81%)
amazon-reviewsSentiment Analysis & Topic Modeling with Amazon Reviews
Stars: ✭ 26 (-39.53%)
100 Days Of Ml CodeA day to day plan for this challenge. Covers both theoritical and practical aspects
Stars: ✭ 172 (+300%)
survHESurvival analysis in health economic evaluation Contains a suite of functions to systematise the workflow involving survival analysis in health economic evaluation. survHE can fit a large range of survival models using both a frequentist approach (by calling the R package flexsurv) and a Bayesian perspective.
Stars: ✭ 32 (-25.58%)
BCESPython module for performing linear regression for data with measurement errors and intrinsic scatter
Stars: ✭ 56 (+30.23%)
MachineLearningImplementations of machine learning algorithm by Python 3
Stars: ✭ 16 (-62.79%)
ML-Experiments整理记录本人担任课程助教设计的四个机器学习实验,主要涉及简单的线性回归、朴素贝叶斯分类器、支持向量机、CNN做文本分类。内附实验指导书、讲解PPT、参考代码,欢迎各位码友讨论交流。
Stars: ✭ 85 (+97.67%)
deep cox mixturesCode for the paper "Deep Cox Mixtures for Survival Regression", Machine Learning for Healthcare Conference 2021
Stars: ✭ 22 (-48.84%)
l2hmc-qcdApplication of the L2HMC algorithm to simulations in lattice QCD.
Stars: ✭ 33 (-23.26%)
em-explanationNotebooks explaining the intuition behind the Expectation Maximisation algorithm
Stars: ✭ 32 (-25.58%)
machine learningA gentle introduction to machine learning: data handling, linear regression, naive bayes, clustering
Stars: ✭ 22 (-48.84%)
go-topicsLatent Dirichlet Allocation
Stars: ✭ 23 (-46.51%)
Stock Market Prediction Web App Using Machine Learning And Sentiment AnalysisStock Market Prediction Web App based on Machine Learning and Sentiment Analysis of Tweets (API keys included in code). The front end of the Web App is based on Flask and Wordpress. The App forecasts stock prices of the next seven days for any given stock under NASDAQ or NSE as input by the user. Predictions are made using three algorithms: ARIMA, LSTM, Linear Regression. The Web App combines the predicted prices of the next seven days with the sentiment analysis of tweets to give recommendation whether the price is going to rise or fall
Stars: ✭ 101 (+134.88%)
PerfSpectsystem performance characterization tool based on linux perf
Stars: ✭ 45 (+4.65%)
fmin adamMatlab implementation of the Adam stochastic gradient descent optimisation algorithm
Stars: ✭ 38 (-11.63%)
geostanBayesian spatial analysis
Stars: ✭ 40 (-6.98%)
GPimGaussian processes and Bayesian optimization for images and hyperspectral data
Stars: ✭ 29 (-32.56%)
mangoParallel Hyperparameter Tuning in Python
Stars: ✭ 241 (+460.47%)
RobustModels.jlA Julia package for robust regressions using M-estimators and quantile regressions
Stars: ✭ 18 (-58.14%)
sparserega collection of modern sparse (regularized) linear regression algorithms.
Stars: ✭ 55 (+27.91%)