GitHub topics: anamoly-detection

Repositories

logpai/awesome-log-analysis

A list of awesome research on log analysis, anomaly detection, fault localization, and AIOps

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prasannaghimiree/Comparision-of-Algorithms-In-Driver-Drowsiness-Detection

Comparision of algorithms in between CNN and SVM for realtime Drowsiness Detection

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Vd1299/Walmart-EDA-and-time-series

Comprehensive EDA and machine learning analysis of Walmart sales data with feature engineering, multiple feature selection techniques, and predictive modeling. Handles 400k+ records with 130+ engineered features to forecast weekly sales and identify key business drivers.

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ADITYASHAH-IITP/Anomaly-Detection-in-Room

Use z-score analysis to find out anomalous behavior in the room by analyzing the condition of the light in your room.

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sushant1827/Credit-Card-Fraud-Detection

Demonstrates the use of ML for Anomaly Detection for Credit Card Transactions: Identifying Fraudulent Activity using Imbalanced Data

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amanovishnu/anamoly-detection-using-decision-classifier 📦

the kdd 99 anomaly detection application is a flask web app that predicts anomalies in the kdd 99 dataset using a decision tree classifier. it allows users to input features for prediction and offers a user-friendly interface with real-time predictions and low latency.

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ericmckevitt/Premier-League-Goal-Prediction

In this project, I am predicting goals scored by Premier League players using a Random Forest Regressor.

Language: Python - Size: 147 MB - Last synced at: 6 months ago - Pushed at: 6 months ago - Stars: 0 - Forks: 0

Guhapriya01/Anamoly-Detection-In-Videos

Language: Python - Size: 148 MB - Last synced at: 4 months ago - Pushed at: about 1 year ago - Stars: 1 - Forks: 0

yliang725/Anomaly-Detection-IoT23

A research project of anomaly detection on dataset IoT-23

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ThecoderPinar/Credit-Card-Fraud-Detection-Project

This project focuses on the detection of credit card fraud using various data science and machine learning techniques. The dataset includes a record of credit card transactions over a specific period, with the goal of accurately identifying fraudulent activities. 🚀✨

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dataninsight/EDA

Simplilearn (EDA) - Masters in Data Science - Assignment

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Azure-Samples/real-time-monitoring-and-observability-for-media

Media streaming for live and video-on-demand playback requires near real-time identification of and response to application problems. This architecture provides real-time monitoring and observability of systems of end-user device telemetry data with anomaly detection.

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NavuluriBalaji/Anomaly-Detection-in-Voice-Conversations

A project on anomaly detection in voice conversations aims to develop algorithms that can automatically detect unusual patterns or behaviors in spoken interactions, helping identify potential threats, anomalies, or aberrations in real-time communication

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rahulbhoyar1995/Anomaly-Detection-in-Transactions

Detect anomalies in transactional data using advanced statistical methods and machine learning algorithms. Enhance fraud detection and anomaly identification in financial transactions for improved security and risk management.

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yashwanth-alapati/Anamoly-detection

driver stats

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PERAMPRAKASH/Anomaly-detection-in-video-surveillance-for-public-safety

Language: Python - Size: 6.84 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

Surbh77/Anamoly-Detection

Teaming up with Generative AI and RAG, we've developed a cutting-edge solution to streamline telecom network performance analysis. Our innovation provides real-time insights, empowering engineers to resolve issues swiftly and boost network efficiency. Stay tuned for more updates on how our project is making waves in the industry!

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sugatagh/Anomaly-Detection-in-Credit-Card-Transactions

The objective of the project is to detect anomalies in credit card transactions. More precisely, given the data on time, amount and 28 transformed features, our goal is to fit a probability distribution based on authentic transactions, and then use it to correctly identify a new transaction as authentic or fraudulent.

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qitianwu/GraphOOD-GNNSafe

The official implementation for ICLR23 paper "GNNSafe: Energy-based Out-of-Distribution Detection for Graph Neural Networks"

Language: Python - Size: 2.37 MB - Last synced at: about 1 year ago - Pushed at: almost 2 years ago - Stars: 64 - Forks: 4

fahadsohrab/mssvdd

Multimodal Subspace Support Vector Data Description

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fahadsohrab/ssvdd

Subspace Support Vector Data Description

Language: MATLAB - Size: 315 KB - Last synced at: over 1 year ago - Pushed at: over 3 years ago - Stars: 4 - Forks: 2

sahaavi/Network-Intrusion-Detection

An Anomaly-based intrusion detection system using Deep Learning

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AHBRIJESH/Mean_Shift_Algorithm

This repository contains a Python notebook that demonstrates the use of the Mean Shift clustering algorithm for image segmentation. Mean Shift is a non-parametric clustering algorithm widely used in computer vision tasks.

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bharathsudharsan/Tiny-Impute

On-device Hybrid Anomaly Detection and Data Imputation

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sharmaroshan/SECOM-Detecting-Defected-Items

Anamoly Detection for Detecting Defected Manufactured Semi-Conductors, as in this case of Classification, the Defected Chips would be very less in comparison to perfect Chips so we have apply either Over-Sampling or Under-Sampling.

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sharmaroshan/Credit-Card-Fraud-Detection

It is Based on Anamoly Detection and by Using Deep Learning Model SOM which is an Unsupervised Learning Method to find patterns followed by the fraudsters.

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pankush9096/kaggle-Credit-Card-Fraud-Detection

This is an highly imbalanced data with only 1.72% minority and 98.28% majority class, i will be explaining Up and down sampling and effect of sampling before and while doing cross validation. Model has been evaluated using precision recall curve.

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alonfirestein/Network-Attack-Anomaly-Detection

Detecting attacks from network data from physical hosts and finding which hosts are anomalous/ outliers

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sharmaroshan/Fraud-Detection-in-Online-Transactions

Detecting Frauds in Online Transactions using Anamoly Detection Techniques Such as Over Sampling and Under-Sampling as the ratio of Frauds is less than 0.00005 thus, simply applying Classification Algorithm may result in Overfitting

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slothengineer/MachineLearning-concepts

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ZhenyuWangg/-Anomaly-Detection

Primary using various techniques to finding anomalies in business cases

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Shishir98/StockAnalysis

Stock Analysis, Predective Modelling using LSTM and Anamoly Detection.

Language: Python - Size: 679 KB - Last synced at: almost 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

AnuradhaIyer/AlzheimersCaregiver Fork of nidhijmr/AlzheimersCaregiver

Android app which will help patients with Alzheimer and dementia

Language: Java - Size: 854 KB - Last synced at: almost 2 years ago - Pushed at: about 7 years ago - Stars: 1 - Forks: 1

omkarpawar1430/Anomaly-Detection-Exercise

Explore anomaly detection methods using the Isolation Forest approach in this GitHub project. Learn preprocessing techniques like one-hot encoding and timestamp conversion to enhance data analysis. Apply the algorithm to identify anomalies effectively. Adapt these insights to your own projects.

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