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foudation-of-machine-learning

full-blockchain-solidity-course-py

Ultimate Solidity, Blockchain, and Smart Contract - Beginner to Expert Full Course | Python Edition

gan

Resources and Implementations of Generative Adversarial Nets: GAN, DCGAN, WGAN, CGAN, InfoGAN

generate-nft

Generate-NFT是由B站UP主Philipjhc倾力打造的批量生成NFT的工具

google-research

Google Research

gravityisnotaforce

Visualising the spacetime geodesics of general relativity

helloworldblockchain

HelloworldBlockchain项目架构清晰，文档齐全，中文注释，可读性高，为区块链初学者学习研究而生。HelloworldBlockchain是一个Helloworld级别的区块链公链系统。HelloworldBlockchain是一个Helloworld级别的数字货币项目。HelloworldBlockchain开发调试简单，下载源码，导入idea(eclipse)，无需任何配置，找到启动类文件com.xingkaichun.helloworldblockchain.explorer.HelloWorldBlockchainExplorerApplication，右键运行，即可启动项目。

heteroscedasticdropoutuncertainty

Demos demonstrating the difference between homoscedastic and heteroscedastic regression with dropout uncertainty.

higher

higher is a pytorch library allowing users to obtain higher order gradients over losses spanning training loops rather than individual training steps.

imgclsmob

Sandbox for training convolutional networks for computer vision

inceptiontime

InceptionTime: Finding AlexNet for Time Series Classification

informationtheoryexperiment

Code used for information theory analysis of deep neural networks using matrix--based renyi's entropy and tensor kernels.

iterative-stratification

scikit-learn cross validators for iterative stratification of multilabel data

kats

Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics, detecting change points and anomalies, to forecasting future trends.

keras-nasnet

"NASNet" models in Keras 2.0+ with weights

keras-radam

RAdam implemented in Keras & TensorFlow

keras-stochastic-weight-averaging

Keras callback function for stochastic weight averaging

keras_bag_of_tricks

Bag of Tricks for Image Classification with Convolutional Neural Networks in Keras

lead

The implementation of the paper 'Multi-label learning by exploiting label dependency' in KDD 2010, an algorithm for multi-label by exploiting label dependency through bayesian network(DAG)

learn-smartcontracts-yt

lightml.jl

Minimal and clean examples of machine learning algorithms implemented in Julia

lizhi

李志所有歌曲下载地址

loss-landscape

Code for visualizing the loss landscape of neural nets

machine-learning-interview

算法工程师-机器学习面试题总结

machine_learning_refined

Notes, examples, and Python demos for the textbook "Machine Learning Refined" (published by Cambridge University Press).

master-thesis-bayesiancnn

Master Thesis on Bayesian Convolutional Neural Network using Variational Inference

materials

mbrce

Matrix-based Rényi's Cross-Entropy

meddsn

meduncertainty

Uncertainty in Medical Image Analysis