Time-Series Anomaly Detection Comprehensive Benchmark

Code for machine learning workshop given to Sanger Systems group

Project for all of the datacamp projects/tutorials that I've worked on

Chris Titus Tech's Windows Utility - Install Programs, Tweaks, Fixes, and Updates

Jobs_Applier_AI_Agent_AIHawk aims to easy job hunt process by automating the job application process. Utilizing artificial intelligence, it enables users to apply for multiple jobs in a tailored way.

💻 PostScript Preview is an extension that helps to preview EPS and PS files in Visual Studio Code.

An extremely fast Python package and project manager, written in Rust.

Use RMarkdown to generate PDF Conference Posters via HTML

A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques

A Python toolkit for rule-based/unsupervised anomaly detection in time series

Neural Networks: Zero to Hero

Python library to manage LUNA's OBR-4600. Focused on distributed sensing. Both acquiring and posprocessing of data

Ocean Data Quality Assessment through Outlier Detection-enhanced Active Learning

An add-on to LaTeX Workshop that provides some features that go beyond the bare essentials

Matplotlib Jupyter Integration

A library for creating and running 3D FEA simulations using the opensource Calculix FEA Package.

Tesseract documentation

This dataset contains six types of events, including background noise, digging, knocking, shaking, watering and walking, with a total of 15,612 samples. We also publicize codes for two common basel…

SKAB - Skoltech Anomaly Benchmark. Time-series data for evaluating Anomaly Detection algorithms.

A package for processing signals recorded using wearable sensors, such as Electrocardiogram (ECG), Photoplethysmogram (PPG), Electrodermal activity (EDA) and 3-axis acceleration (ACC).

🚀 Generate GitHub profile README easily with the latest add-ons like visitors count, GitHub stats, etc using minimal UI.

Functions for computing metrics commonly used in the field of out-of-distribution (OOD) detection

📗 The Code Smells Catalog

Algorithms for outlier, adversarial and drift detection

Apply modern, deep learning techniques for anomaly detection to identify network intrusions.

A python library for user-friendly forecasting and anomaly detection on time series.

List of tools & datasets for anomaly detection on time-series data.

1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.

A toolkit for machine learning from time series