Real time peak detection with z-score for Arduino
Minimal A/B Testing Library in PHP
Anthropometric z-score calculator
A collection of Python scripts demonstrating core statistical concepts like percentile analysis, Z-scores, modified Z-tests, and cosine similarity with real datasets and visualizations.
Identification of meritorious students in primary education
A Qt port of the peak detection algorithm demo from https://stackoverflow.com/a/22640362, with interactive parameters.
CNN autoencoder is trained on the MNIST numbers dataset for image reconstruction. Anomaly detection is carried out by calculating the Z-score. The framework used is Keras.
Android app testing reaction times during awake brain surgeries
An implementation of Monroe et al., 2008.
Anomaly detection in synthetic transaction and sales data with Python. Generates realistic data, injects unusual events, and applies Isolation Forest, Local Outlier Factor, and Z-score methods to detect outliers. Produces anomaly reports and visualizations for portfolio-ready demonstration of data science skills.
🔢 Anomaly detection service for Google Cloud Monitoring metrics, utilising statistical analysis to identify significant deviations in time-series data
Outlier detection (z-score and IQR) and visualization on Geolife dataset for transport mode detection task
Retrieving, Processing, and Visualizing Data with Python
Computational programs and algorithms used to convert information from biochemical experiments (DNA/RNA/Protein/DNA chip/NGS) into useful information and data.
This project uses statistical analysis to detect fraudulent credit card transactions by examining patterns and anomalies in a dataset of 10,000 transactions, calculating averages, medians, frequencies, and identifying outliers to distinguish between legitimate and fraudulent activities.
Use z-score analysis to find out anomalous behavior in the room by analyzing the condition of the light in your room.
Undergraduate Project - Statistical Outlier Detection Methods
Analysis of Classical Machine Learning Algorithms for Anomaly Detection in Time Series Data
A TensorFlow 2 Implemention of Deep Adaptive Input Normalization for Time Series Using Keras API
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