Stars
Source code for multichaind, multichain-cli and multichain-util.
Simple, Pythonic remote execution and deployment.
Hyperledger Fabric is an enterprise-grade permissioned distributed ledger framework for developing solutions and applications. Its modular and versatile design satisfies a broad range of industry u…
Framework to easily implement decentralized peer-to-peer network applications in Python
Javascript like setTimeout and setInterval for c++ developers
My implementation of a blockchain in C++ - Peer-to-Peer network, SHA-256, Merkle Trees, Mining, etc.
Ultimate Solidity, Blockchain, and Smart Contract - Beginner to Expert Full Course | Python Edition
Ethereum Proof-of-Stake Consensus Specifications
Transfer Learning Shootout for PyTorch's model zoo (torchvision)
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
Deep learning anomaly detection on spatio-temporal AIS data by combining a multi-headed self-attention structure with bidirectional long short term memory(BLSTM) into a Variational Autoencoder (VAE).
Creates several arp-scan commands to help locate an unused IP address on a LAN
CICFlowmeter-V4.0 (formerly known as ISCXFlowMeter) is an Ethernet traffic Bi-flow generator and analyzer for anomaly detection that has been used in many Cybersecurity datsets such as Android Adwa…
Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoe…
Learn to build your neural network using PyTorch
Pytorch Implementation of Adversarial Autoencoder
1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
Anomaly detection for streaming data using autoencoders
iPython notebook and pre-trained model that shows how to build deep Autoencoder in Keras for Anomaly Detection in credit card transactions data
A wizard's guide to Adversarial Autoencoders
neural networks for unsupervised anomaly detection in computer networks. written in pytorch.