This portfolio contains projects, course, and code for my deep learning practices
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Updated
Mar 3, 2019 - Python
This portfolio contains projects, course, and code for my deep learning practices
Using public data, I implement different ML algorithms and techniques
Les cartes topologiques ou auto-organisatrices font partie de la famille des modèles dits à «apprentissage non supervisé», c’est-à-dire qui s’appliquent sur des données dont on connaît le domaine sur lequel porte le recueil statistique, mais pour lesquelles les connaissances a priori ne sont pas totalement organisées., les données en groupements…
This is my course project for EE404 Soft Computing
Self organizing maps (SOM) in Python3.
Modified versions of Self organizing map and Learning vector quantization
The report I wrote for a BSc project called "A computational framework for the investigation of large-scale brain organisation"
Lab exercise for Neural Networks study. Includes Self-Organizing map, Hopfield network and Back-Propagation network
Use Deep Learning Methods to analyze gene based microarray data to make classifcations on diseases, especially cancers, where the model is going to identify cancer stages for different cancers.
fraud detection with SOMs
Ingenieria del conocimiento
Native Java implementation of a self-organizing network (SON) for clustering.
Self organizing maps
Python implementation of the unsupervised Deep Learning Algorithm SOM
Self-Organizing Maps(SOM) or self-organizing feature map (SOFM) is a type of artificial neural network (ANN) that is trained using unsupervised learning. Using R.
Traveling Salesman Problem with Self-Organizing Maps
Solving the Traveling Salesman Problem using Self-Organizing Maps
Кластеризация вузов средствами построения карты Кохонена
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