vidagharavian

alfia.server

ansible

caption_image_generator

cloud_service

django-celery-docker-example

Example Docker setup for a Django app behind an Nginx proxy with Celery workers

FUM-Android-Course

Basic Android Course Resources at Ferdowsi University of Mashhad; Esfand 1396

gaussian_mixture_model

a brief summary of Gaussian mixture models. for more information about what this code does exactly ,please check the document file.

GNNComparision

image_processing

WSNGNN

vidagharavian/alfia.server

vidagharavian/ansible

vidagharavian/caption_image_generator

vidagharavian/cloud_service

vidagharavian/django-celery-docker-example

Example Docker setup for a Django app behind an Nginx proxy with Celery workers

vidagharavian/FUM-Android-Course

Basic Android Course Resources at Ferdowsi University of Mashhad; Esfand 1396

vidagharavian/gaussian_mixture_model

a brief summary of Gaussian mixture models. for more information about what this code does exactly ,please check the document file.

vidagharavian/GNNComparision

vidagharavian/graph_clustring

a brief summary about graph_clustring basics

vidagharavian/image_processing

vidagharavian/kmeans

propess of this code is learning some basic information about kmeans not just the function that we all probaby use but also definition of kmean and what it exactly does.

vidagharavian/WSNGNN

vidagharavian/linkage

The following linkage methods are used to compute the distance between two clusters s and d. i explained more about this algorithm in the following document that i add below

vidagharavian/Mahalanobis_distance

The Mahalanobis distance is a measure of the distance between a point P and a distribution D, introduced by P. C. Mahalanobis in 1936.[1] It is a multi-dimensional generalization of the idea of measuring how many standard deviations away P is from the mean of D. This distance is zero if P is at the mean of D, and grows as P moves away from the mean along each principal component axis. If each of these axes is re-scaled to have unit variance, then the Mahalanobis distance corresponds to standard Euclidean distance in the transformed space. The Mahalanobis distance is thus unitless and scale-invariant, and takes into account the correlations of the data set. i added some more explanation about code right in document file.

vidagharavian/min_shift_clustring

min_shift algorithm is a clustering method .i tried to take closer look on this algorithm

vidagharavian/nlp

vidagharavian/RBFS_KNN

execution of knn algorithm in rbfspase

vidagharavian/recomendation_system

vidagharavian/servises