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7-adimlik-yapay-zeka-yolculugu

7 ADIMLIK YAPAY ZEKA YOLCULUGU

algorithm-reconize-vertebral-collumn

Algorithm developed as step of calculate Cobb angle. This algorithm will recognize the vertebral collumn tracing a line on vertebral collumn

contrastive-unpaired-translation

Contrastive unpaired image-to-image translation, faster and lighter training than cyclegan (ECCV 2020, in PyTorch)

deblurgan

imported from https://github.com/KupynOrest/DeblurGAN.git

dicom-to-jpg

Convert all DICOM (.dcm) images in a folder to JPG/PNG and extract all patients information in a '.csv' format in a go using python.

dlwpt-code

Code for the book Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann.

horseracingprediction

Using Support Vector regression algorithm to predict horse racing results

imagecaptioning.pytorch

image captioning codebase in pytorch(finetunable cnn in branch "with_finetune";diverse beam search can be found in 'dbs' branch; self-critical training is under my self-critical.pytorch repository.)

imgaug

Image augmentation for machine learning experiments.

learning-data-mining-with-python-second-edition

Learning Data Mining with Python Second Edition by Packt

liverseg-2017-nipsws

Detection-aided Liver Lesion Segmentation

machinelearningformedicalimages

Example code on how to apply machine learning methods to medical images. Contains code (python and python notebooks) and data (DICOM)

medical-image-analysis-ipython-tutorials

medical-image-analysis-ipython-tutorials-1

pneumonia-diagnosis-using-xrays-96-percent-recall

BEST SCORE ON KAGGLE SO FAR , EVEN BETTER THAN THE KAGGLE TEAM MEMBER WHO DID BEST SO FAR. The project is about diagnosing pneumonia from XRay images of lungs of a person using self laid convolutional neural network and tranfer learning via inceptionV3. The images were of size greater than 1000 pixels per dimension and the total dataset was tagged large and had a space of 1GB+ . My work includes self laid neural network which was repeatedly tuned for one of the best hyperparameters and used variety of utility function of keras like callbacks for learning rate and checkpointing. Could have augmented the image data for even better modelling but was short of RAM on kaggle kernel. Other metrics like precision , recall and f1 score using confusion matrix were taken off special care. The other part included a brief introduction of transfer learning via InceptionV3 and was tuned entirely rather than partially after loading the inceptionv3 weights for the maximum achieved accuracy on kaggle till date. This achieved even a higher precision than before.

pratik-derin-ogrenme-uygulamalari

Çeşitli kütüphaneler kullanılarak Türkçe kod açıklamalarıyla TEMEL SEVİYEDE pratik derin öğrenme uygulamaları.

predictive-analytics-with-tensorflow

Predictive Analytics with TensorFlow, published by Packt

ptc5750_ctscan_segmentation_with_cnn

py

Repository to store sample python programs for python learning

python

:snake: Python Programs

pytorch-cyclegan-and-pix2pix

Image-to-Image Translation in PyTorch

pytorch-unet

Tunable U-Net implementation in PyTorch

pytorchneuralstyletransfer

Implementation of Neural Style Transfer in Pytorch

siggraph2016_colorization

Code for the paper 'Let there be Color!: Joint End-to-end Learning of Global and Local Image Priors for Automatic Image Colorization with Simultaneous Classification'.

simpleitk

SimpleITK: a simplified layer build on top of the Insight Toolkit (ITK), intended to facilitate its use in rapid prototyping, education and interpreted languages.

simplerick

🙌 Low-cost 2D ultrasound imaging hardware for makers

style-tranfer

Implementation of original style transfer paper (Gatys et al)

trnltk

Turkish Natural Language Toolkit

unet-segmentation-in-keras-tensorflow

Unet Segmentation