kai010203

kai010203's Stars

• physhik/ecg-mit-bih

  ECG classification using MIT-BIH data, a deep CNN learning implementation of Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network, https://www.nature.com/articles/s41591-018-0268-3 and also deploy the trained model to a web app using Flask, introduced at

  Language:Python17655

• animikhaich/ECG-Atrial-Fibrillation-Classification-Using-CNN

  This is a CNN based model which aims to automatically classify the ECG signals of a normal patient vs. a patient with AF and has been trained to achieve up to 93.33% validation accuracy.

  Language:Jupyter Notebook4718

• lxdv/ecg-classification

  ECG Arrhythmia classification using CNN

  Language:Jupyter Notebook22668

• nerajbobra/lstm-qrs-detector

  CNN-LSTM based QRS detector for ECG signals

  Language:Jupyter Notebook217

• carlsummer/python_developer_tools

  论文复现，多机多卡

  Language:HTML4710

• yanfang-research/ECG-AI

  Code, Dataset, Tools Review

  294

• juxiangwu/image-processing

  Digital Image Processing Learning Notes.

  Language:Jupyter Notebook165

• liyupi/sql-mother

  免费的闯关式 SQL 自学教程网站，从 0 到 1 带大家掌握常用 SQL 语法，纯前端实现，简单易学~

  Language:TypeScript3.1k352

• AUTOMATIC1111/stable-diffusion-webui

  Stable Diffusion web UI

  Language:Python135k25.9k

• ZhangXinNan/LearnPractice

  The more you practice, the better you learn

  Language:Shell187

• ShanaScogin/BayesPostEst

  An R package to generate and plot postestimation quantities after estimating Bayesian regression models using MCMC

  Language:R122

• ncsuSEAL/Bayesian_LSP

  A Bayesian hierarchical model that quantifies long-term annual land surface phenology from sparse time series of vegetation indices.

  Language:R4111

• wasimaftab/LIMMA-pipeline-proteomics

  LIMMA (an empirical Bayes method) pipeline for two group comparison in a proteomic experiment

  Language:R2410

• bbsBayes/bbsBayes

  An R Package for Hierarchical Bayesian Analysis of North American Breeding Bird Survey Data

  Language:R3114

• xylimeng/BayesMAR

  Bayesian Median Autoregressive model for time series forecasting

  Language:R610

• majkamichal/naivebayes

  High performance implementation of the Naive Bayes algorithm in R

  Language:R365

• Bo-Ning/Bayesian-multivariate-time-series-causal-inference

  R code for ''Bayesian method for causal inference in spatially-correlated multivariate time series''

  Language:R4321

• ghanag/HarvardX-Capstone-Project-NYC-House-Price-Forecast

  Language:R11

• SiweiMa/Ames-House-Prices-Multiple-Linear-Regression-Project-in-Python

  Given Ames Housing dataset, the project started with an exploratory data analysis (EDA) to identify the missing values, suspicious data, and redundant variables. Then I performed a mixed stepwise selection to reduce the set of variables and select the best model based on AIC, BIC, and adjust R-squared. With the best model selected, the model assumptions were checked regarding normality, homoscedasticity, collinearity, and linearity between response and predictors. Several solutions were proposed to solve the assumption violation. The model was then tested on unseen data and scored on Root-Mean-Squared-Error (RMSE).

  Language:Jupyter Notebook2

• sjmiller8182/RegressionHousingPrices

  Project using multiple linear regression to model prices of houses in Ames, IA.

  Language:R65

• dipanjanS/practical-machine-learning-with-python

  Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.

  Language:Jupyter Notebook2.2k1.6k

• dipanjanS/data_science_for_all

  Code and resources for my blog and articles to share Data Science and AI knowledge and learnings with everyone

  Language:Jupyter Notebook203209

• developer22-university/NetworkIntrusionDetection

  This project uses various deep learning models, such as FFNN, LSTM, and ESN to enhance the detection of denial of service attacks on the CSE-CIC-IDS2018 datasets.

  22

• Ahamasaleh/Deep-learning-for-intrusion-detection-using-Recurrent-Neural-network-RNN

  Deep Learning techniques can be implemented in the field of cybersecurity to handle the issues related to intrusion just as they have been successfully implemented in the areas such as computer vision and natural language processing (NLP). RNN model is compared with J48, Artificial Neural Network, Random Forest, Support Vector Machine and other machine learning techniques to detect malicious attacks in terms of binary and multiclass classifications.

  Language:Jupyter Notebook225

• rxYoungho/DDOS-ML-Detection

  Long Short-term Memory, Recurrent Neural Network method was used to detect the DDoS attack

  Language:Jupyter Notebook103

• buseyaren/classification-and-detection-ddosattacks

  In this repository, DDOS attacks were detected using Recurrent Neural Networks (LSTM) and Classical Machine Learning Algorithms.

  Language:Jupyter Notebook183

• elifnurkarakoc/CICIDS2017

  CICIDS2017 dataset

  Language:Jupyter Notebook4618

• mahendradata/cicids2017-ml

  The purpose of this repository is to demonstrate the steps of processing CICIDS2017 dataset using machine learning algorithms.

  Language:Jupyter Notebook4817

• lapteva059/colourblind_microservice

  Microservice for image correction on a web page based on an algorithm https://github.com/tsarjak/Simulate-Correct-ColorBlindness for people with colorblindness.

  Language:Python1

• 0xfourzerofour/image-slant-correction

  Image slant and skew correction in OpenCV using 4 point perspective transformation

  Language:Python3