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jupyter-notebook x

151 search results found

Homemade Machine Learning ⭐ 21,542

🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained

The Numenta Anomaly Benchmark

Loglizer ⭐ 1,062

A log analysis toolkit for automated anomaly detection [ISSRE'16]

Telemanom ⭐ 793

A framework for using LSTMs to detect anomalies in multivariate time series data. Includes spacecraft anomaly data and experiments from the Mars Science Laboratory and SMAP missions.

Datastream.io ⭐ 761

An open-source framework for real-time anomaly detection using Python, ElasticSearch and Kibana

Business Machine Learning ⭐ 620

A curated list of practical business machine learning (BML) and business data science (BDS) applications for Accounting, Customer, Employee, Legal, Management and Operations (by @firmai)

Prometheus Anomaly Detector ⭐ 535

A newer more updated version of the prometheus anomaly detector (https://github.com/AICoE/prometheus-anomaly-detec

Azure Sentinel Notebooks ⭐ 485

Interactive Azure Sentinel Notebooks provides security insights and actions to investigate anomalies and hunt for malicious behaviors.

Coursera Ml Using Matlab Python ⭐ 460

coursera吴恩达机器学习课程作业自写Python版本+Matlab原版

Hands On Data Analysis With Pandas ⭐ 390

Materials for following along with Hands-On Data Analysis with Pandas.

Credit Card Fraud Detection Using Autoencoders In Keras ⭐ 289

iPython notebook and pre-trained model that shows how to build deep Autoencoder in Keras for Anomaly Detection in credit card transactions data

Log Anomaly Detector ⭐ 278

Log Anomaly Detection - Machine learning to detect abnormal events logs

Htmpapers ⭐ 261

Numenta published papers code and data

Extended Isolation Forest for Anomaly Detection

Deep Learning For Hackers ⭐ 196

Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT)

Lstm_anomaly_thesis ⭐ 191

Anomaly detection for temporal data using LSTMs

My attempt at reproducing the paper Deep Autoencoding Gaussian Mixture Model for Unsupervised Anomaly Detection

DAGMM Tensorflow implementation

Repo 2019 ⭐ 135

BERT, AWS RDS, AWS Forecast, EMR Spark Cluster, Hive, Serverless, Google Assistant + Raspberry Pi, Infrared, Google Cloud Platform Natural Language, Anomaly detection, Tensorflow, Mathematics

Vae Lstm For Anomaly Detection ⭐ 128

We propose a VAE-LSTM model as an unsupervised learning approach for anomaly detection in time series.

Data Science Portfolio ⭐ 125

A Portfolio of my Data Science Projects

Humanbehaviorbku ⭐ 116

Abnormal Human Behaviors Detection/ Road Accident Detection From Surveillance Videos/ Real-World Anomaly Detection in Surveillance Videos/ C3D Feature Extraction

Anomaliesinoptions ⭐ 113

In this notebook we will explore a machine learning approach to find anomalies in stock options pricing.

Business Analytics Ime654 ⭐ 106

Course homepage for "Business Analytics (IME654)" @Korea University

Anomaly Detection ⭐ 100

Anomaly detection algorithm implementation in Python

Cyber Security ⭐ 89

Machine Learning for Network Intrusion Detection & Misc Cyber Security Utilities

Repository for the One class neural networks paper

Anomalydetector ⭐ 88

Samples for the Anomaly Detection API documentation:

Keras Oneclassanomalydetection ⭐ 79

[5 FPS - 150 FPS] Learning Deep Features for One-Class Classification (AnomalyDetection). Corresponds RaspberryPi3. Convert to Tensorflow, ONNX, Caffe, PyTorch. Implementation by Python + OpenVINO/Tensorflow Lite.

Adversarially Learned Anomaly Detection ⭐ 79

ALAD (Proceedings of IEEE ICDM 2018) official code

Ace_azure_ml ⭐ 78

This repository contains training material related to Azure and Machine Learning

Detection of Accounting Anomalies using Deep Autoencoder Neural Networks - A lab we prepared for NVIDIA's GPU Technology Conference 2018 that will walk you through the detection of accounting anomalies using deep autoencoder neural networks. The majority of the lab content is based on Jupyter Notebook, Python and PyTorch.

Anomatools ⭐ 71

Toolbox for anomaly detection.

Anomaly Reactionrl ⭐ 69

Using RL for anomaly detection in NSL-KDD

Machine Learning Netflow ⭐ 62

Ipython notebook that illustrates effectiveness of machine learning algorithms in anomaly detection of netflow data (inbound/outbound DDoS, etc...)

Unsupervised_anomaly_detection ⭐ 60

A Notebook where I implement differents anomaly detection algorithms on a simple exemple. The goal was just to understand how the different algorithms works and their differents caracteristics.

Homemade Machine Learning Cn ⭐ 60

自制机器学习

anomaly detection with GAN

Predictive Maintenance ⭐ 56

Datasets for Predictive Maintenance

Fraud_detection_techniques ⭐ 53

Threat Hunting With Notebooks ⭐ 47

Repository with Sample threat hunting notebooks on Security Event Log Data Sources

mmFall: Fall Detection using 4D MmWave Radar and Variational Recurrent Autoencoder

Oc Nn_old ⭐ 44

Models for one class neural networks

Elections ⭐ 41

Statistical anomalies in Russian elections

Anomaly_detection ⭐ 39

This is a times series anomaly detection algorithm, implemented in Python, for catching multiple anomalies. It uses a moving average with an extreme student deviate (ESD) test to detect anomalous points.

High Dimensional Deep Learning ⭐ 39

Science des données Saison 4 : Apprentissage en grande dimension, Données fonctionnelles, Détection d'anomalies, Introduction au Deep Learning

Jupyter2kibana ⭐ 38

A Workflow for Data Scientists to bring Jupyter Notebook Visualizations to Kibana Dashboards

Metric_learning ⭐ 33

Metric Learning App Dev Resource

Tilitools ⭐ 33

[ti]ny [li]ttle machine learning [tool]box - Machine learning, anomaly detection, one-class classification, and structured output prediction

Iso_forest ⭐ 33

Simple implementation of Isolation Forest

Satellite Telemetry Anomaly Detection ⭐ 33

Unsupervised machine learning techniques for detecting anomalies in LASP spacecraft telemetry

Arcticseals ⭐ 31

A deep learning project in cooperation with the NOAA Marine Mammal Lab to detect & classify arctic seals in aerial imagery to understand how they’re adapting to a changing world.

Power Laws Anomalies ⭐ 30

Lsanomaly ⭐ 29

lsanomaly, a probabilistic anomaly detector for Python.

Anomaly_tuning ⭐ 29

Learning hyperparameters for unsupervised anomaly detection

models and evaluation framework for trending topics detection

Federated Ml ⭐ 26

Detect anomalies in network traffic data using Federated Machine Learning technique.

Time Series Analysis With Python 3.x ⭐ 26

Time Series Analysis with Python 3.x [Video], published by Packt

A tool for anomaly detection over streaming data based on sentiment analysis

Tinyml Example Anomaly Detection ⭐ 25

TinyML example showing how to do anomaly detection with Python and Arduino

Anomaly_detection ⭐ 25

Detection of Accounting Anomalies in the Latent Space using Adversarial Autoencoder Neural Networks - A lab we prepared for the KDD'19 Workshop on Anomaly Detection in Finance that will walk you through the detection of interpretable accounting anomalies using adversarial autoencoder neural networks. The majority of the lab content is based on Jupyter Notebook, Python and PyTorch.

Beginning Anomaly Detection Using Python Based Dl ⭐ 23

Source Code for 'Beginning Anomaly Detection Using Python-Based Deep Learning' by Sridhar Alla and Suman Kalyan Adari

Kaspersky_hackathon ⭐ 23

https://events.kaspersky.com/hackathon/

Reinforcement Learning for Anomaly Detection

Anomaly Xray Gans ⭐ 22

Anomaly detection on X-Ray MURA dataset using GAN.

Bothound ⭐ 22

Automatic attack detector and botnet classifier

Exp Anomaly Detector ⭐ 21

The design of a time series anomaly detector through RNN and RL.

Machine_learning_from_scratch_matlab_python ⭐ 21

Vectorized Machine Learning in Python 🐍 From Scratch

Pycurious ⭐ 21

Python package for computing the Curie depth from the magnetic anomaly

2018aicity_mcprl ⭐ 20

F Anogan_with_pytorch ⭐ 20

Source code for the ACML 2019 paper "Functional Isolation Forest".

Pidforest ⭐ 19

Code for the PIDForest algorithm for anomaly detection

Ml Based Anomaly Detection ⭐ 18

Spectral Residual

Time Series Anomaly ⭐ 17

Anomaly detection on time series using Deep Learning techniques

Autoencoder_vs_metriclearning ⭐ 17

AutoEncoder vs Metric Learning for Anomaly Detection

Exp Anomaly Detector Aiops ⭐ 17

Using DNN for univariate time series anomaly detection over AIOps Competition dataset

Anomaly Detection For Keystroke Dynamics ⭐ 16

Comparing Anomaly-Detection Algorithms for Keystroke Dynamics based on http://www.cs.cmu.edu/~keystroke/

Faster Grad Cam ⭐ 16

Faster and more precisely than Grad-CAM

Probingdataset ⭐ 16

Dataset of Probing Attacks (Port Scan) performed with nmap, unicornscan, hping3, zmap and masscan

Pydata2016 ⭐ 16

A couple projects using scikit-learn illustrating project decision making.

More Ml Algorithm ⭐ 16

There are more Machine Learning algorithms

Calculate Precipitation Based Agricultural Drought Indices With Python ⭐ 16

Precipitation-based indices are generally considered as the simplest indices because they are calculated solely based on long-term rainfall records that are often available. The mostly used precipitation-based indices consist of Decile Index (DI) Hutchinson Drought Severity Index (HDSI) Percen of Normal Index (PNI) Z-Score Index (ZSI) China-Z Index (CZI) Modified China-Z Index (MCZI) Rainfall Anomaly Index (RAI) Effective Drought Index (EDI) Standardized Precipitation Index (SPI).

Machine Learning Excercise Notebook Python ⭐ 15

Andrew Ng机器学习对应Python Jupyter Notebook

Pydetect ⭐ 15

Change point and anomaly detections for time-series

Data_analysis_tutorial ⭐ 15

Efficient_gan Based_anomaly_detection_keras ⭐ 14

Pytorch implementation of GEE: A Gradient-based Explainable Variational Autoencoder for Network Anomaly Detection

Applied Ai Study Group 2020 June ⭐ 13

This is the repository for the content of inzva 2020-June Applied AI Study Group, guided by Ahmet Melek and Onur Boyar.

Real Time Implementation Of Gunshot Detection System ⭐ 13

Real Time Implementation of Gunshot Detection System

Stream Anomaly Detect ⭐ 13

Implementation of algorithms proposed by [Huang and Kasiviswanathan]

Unsupervised Anomaly Detection for X-Ray Images

Cool Papers In Pytorch ⭐ 12

Reimplementing cool papers in PyTorch...

Time Series Anomaly Detection Toolkit

Feature Engineering For Fraud Detection ⭐ 12

Implementation of feature engineering from Feature engineering strategies for credit card fraud

Gan Yhat ⭐ 12

GAN implementations

PyTorch implementation of paper: adVAE: a Self-adversarial Variational Autoencoder with Gaussian Anomaly Prior Knowledge for Anomaly Detection

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