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animegan

A simple PyTorch Implementation of Generative Adversarial Networks, focusing on anime face drawing.

augmentor

Image augmentation library in Python for machine learning.

awesome-image-classification

A curated list of deep learning image classification papers and codes

awesome-paper

Summary fo current algorithms of Artificial Intelligence. The key to Jarvis, the key to Future!!!Yes, We are huge fans of Ironman

awesome-random-forest

Random Forest - a curated list of resources regarding random forest

bag-of-local-features-models

Pretrained bag-of-local-features neural networks

bookcnn

《深度卷积网络：原理与实践》现已在淘宝天猫京东当当发售. 这里是其中的代码下载.

calcaic

モデル評価指標であるAIC(Akaike's Information Criterion)の計算をPythonで実装した．

centos-ubuntu-io

circrna

deep-learning-papers-reading-roadmap

Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!

deep-learning-papers-translation

深度学习论文翻译，包括分类论文，检测论文等

deeping-flow

Deep-learning by using TensorFlow. Basic nns like Logistic, CNN, RNN, LSTM and some examples are implemented by complex model.

deepobs

DeepOBS: A Deep Learning Optimizer Benchmark Suite

drees

DREES (Dose response explorer system) is an in-house Matlab-based open source software customized for modeling and exploring dose response in radiation oncology.

esrgan

ECCV18 Workshops - Enhanced SRGAN. Champion PIRM Challenge on Perceptual Super-Resolution. The training codes are in BasicSR.

feature-extraction

Computer vision feature extraction toolbox for image classification

feature-extraction-using-image-processing-and-classification-based-on-machine-learning-algorithms

Image Processing, machine learning

geo

git

Git Source Code Mirror - This is a publish-only repository and all pull requests are ignored. Please follow Documentation/SubmittingPatches procedure for any of your improvements.

handle_imabalnce_class

Address imbalance classes in machine learning projects.

hello-world

hypothesis-tests-in-r

A #glfintech R turorial on statistics discussing hypothesis tests - parametric tests (z-test, t-test and ANOVA) and non-parametric tests (Mann-Whitney Test, Wilcoxon Rank-sum test, Wilcoxon Signed-rank Test, Kruskal Wallis Test).

identifying-interstitial-lung-diseases-using-image-processing-

To design a system that retrieves similar images using the image features such as the Gabor Wavelet and Discrete Wavelet transform. The system is basically built for identifying lung diseases using the CT scans of the lungs, the existing CT scan images of the diseases are taken into the database and the feature extraction process is done upon them the values are stored in a matrix and then in the end these values of database images are compared with the query image and by using the similarity metric (manhattan distance), the most relative image is retrieved.

iic

Invariant Information Clustering for Unsupervised Image Classification and Segmentation

illustrationgan

A simple, clean TensorFlow implementation of Generative Adversarial Networks with a focus on modeling illustrations.

image-segmentation

Image segmentation, feature extraction, and SVM classification

imbalanced-learn

A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning

imgaug

Image augmentation for machine learning experiments.

implementation_variational-auto-encoder

Simple implementation of Variational Autoencoder