onuralpyigit

cnn-text-classification-tf

Convolutional Neural Network for Text Classification in Tensorflow

Code_Quality_and_Analysis_Training

Continual-Normalization

CreditCardFraudDetection

Detect payment fraud on credit card transactions

DDS-ReliabilityEstimation

Fast-DDS

The most complete DDS - Proven: Plenty of success cases.

github-demo

A simple demo repository to show the basic Git workflow

jhipster

memoryReferences

small project to see differences between reference types

SoftwareAsAGraph

Represent a software as a graph in order to detect design defects

onuralpyigit/SoftwareAsAGraph

Represent a software as a graph in order to detect design defects

onuralpyigit/cnn-text-classification-tf

Convolutional Neural Network for Text Classification in Tensorflow

onuralpyigit/Code_Quality_and_Analysis_Training

onuralpyigit/Continual-Normalization

onuralpyigit/CreditCardFraudDetection

Detect payment fraud on credit card transactions

onuralpyigit/DDS-ReliabilityEstimation

onuralpyigit/Fast-DDS

The most complete DDS - Proven: Plenty of success cases.

onuralpyigit/github-demo

A simple demo repository to show the basic Git workflow

onuralpyigit/jhipster

onuralpyigit/memoryReferences

small project to see differences between reference types

onuralpyigit/Near-State-of-the-Art-results-on-classifying-EuroSAT-satellite-images-using-Keras

onuralpyigit/Python-Practical-Application-on-Climate-Variability-Studies

This tutorial is a companion volume of Matlab versionm but add more. Main objective is the transference of know-how in practical applications and management of statistical tools commonly used to explore meteorological time series, focusing on applications to study issues related with the climate variability and climate change. This tutorial starts with some basic statistic for time series analysis as estimation of means, anomalies, standard deviation, correlations, arriving the estimation of particular climate indexes (Niño 3), detrending single time series and decomposition of time series, filtering, interpolation of climate variables on regular or irregular grids, leading modes of climate variability (EOF or HHT), signal processing in the climate system (spectral and wavelet analysis). In addition, this tutorial also deals with different data formats such as CSV, NetCDF, Binary, and matlab'mat, etc. It is assumed that you have basic knowledge and understanding of statistics and Python.

onuralpyigit/rasterio

Rasterio reads and writes geospatial raster datasets

onuralpyigit/repo

This repository contains all the source code for http://www.source4code.info

onuralpyigit/ScalaHelloWorld

onuralpyigit/siml

Machine Learning algorithms implemented from scratch

onuralpyigit/SmartMenu

onuralpyigit/starter-web

Simple starting point website project based upon Initializr

onuralpyigit/tensorflow

Computation using data flow graphs for scalable machine learning