martian1231

blackeye

The ultimate phishing tool with 38 websites available!

auto-sklearn

Automated Machine Learning with scikit-learn

h2o-3

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

wifiphisher

The Rogue Access Point Framework

lscript

The LAZY script will make your life easier, and of course faster.

sherlock

Hunt down social media accounts by username across social networks

phoneinfoga

Information gathering framework for phone numbers

breach-parse

A tool for parsing breached passwords

h8mail

Email OSINT & Password breach hunting tool, locally or using premium services. Supports chasing down related email

Anonymous

byob

An open-source post-exploitation framework for students, researchers and developers.

pandoc

Universal markup converter

interfacegan

[CVPR 2020] Interpreting the Latent Space of GANs for Semantic Face Editing

stylegan-encoder

StyleGAN Encoder - converts real images to latent space

stylegan

StyleGAN - Official TensorFlow Implementation

voicemap

Identifying people from small audio fragments

practical-pytorch

Go to https://github.com/pytorch/tutorials - this repo is deprecated and no longer maintained

catboost

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

HRNet-Semantic-Segmentation

The OCR approach is rephrased as Segmentation Transformer: https://arxiv.org/abs/1909.11065. This is an official implementation of semantic segmentation for HRNet. https://arxiv.org/abs/1908.07919

albumentations

Fast and flexible image augmentation library. Paper about the library: https://www.mdpi.com/2078-2489/11/2/125

Practical-DRL

This is a practical resource that makes it easier to learn about and apply Practical Deep Reinforcement Learning (DRL) https://ibrahimsobh.github.io/Practical-DRL/

segmentation_models

Segmentation models with pretrained backbones. Keras and TensorFlow Keras.

imgaug

Image augmentation for machine learning experiments.

image-segmentation-keras

Implementation of Segnet, FCN, UNet , PSPNet and other models in Keras.

Anchor-Boxes-with-KMeans

How to initialize Anchors in Faster RCNN for custom dataset?

data-science-interviews

Data science interview questions and answers

hiplot

HiPlot makes understanding high dimensional data easy