Data and code for our analysis of DermaMNIST (MedMNIST), HAM10000, and Fitzpatrick17k datasets
Introduction to Machine Learning with Python
A burp suite extension that reviews backup, old, temporary and unreferenced files on web server for sensitive information (OWASP WSTG-CONF-04, OTG-CONFIG-004)
Code associated with the paper 'Cracking the blackbox of deep sequence-based protein-protein interaction prediction'
Safe Data Leakage via Application Background Screenshot and Prevent Screenshot for Android and iOS.
A PHP client example to snapWONDERS API. Perform deep digital media analysis, reveal hidden metadata, hidden metadata, copyrights, steganography and private information leakage.
A Go client example to snapWONDERS API. Perform deep digital media analysis, reveal hidden metadata, hidden metadata, copyrights, steganography and private information leakage.
A Python client example to snapWONDERS API. Perform deep digital media analysis, reveal hidden metadata, hidden metadata, copyrights, steganography and private information leakage.
A C# client example to snapWONDERS API. Perform deep digital media analysis, reveal hidden metadata, hidden metadata, copyrights, steganography and private information leakage.
Optimize your web vulnerability assessments with PassiveDigger, a comprehensive Burp Suite extension that specializes in passive traffic analysis. Detect potential vulnerabilities, get actionable insights, and supercharge your security audits.
Study the relationship between review numbers and sales for Steam games
This is me learning how to quickly improve the quality of my models.
School Project for DLP class
A static analysis tool to detect test data leakage in Python notebooks
How to deal with Missing Values, Categorical Variables, Pipelines, Cross-Validation, XGBoost, Data Leakage
I recommend you take privacy seriously... Unless you want me to sort the data ;)
Think of Local sheriff as a recon tool in your browser (WebExtension). While you normally browse the internet, Local Sheriff works in the background to empower you in identifying what data points (PII) are being shared / leaked to which all third-parties.
Used R to analyze, explore and process the data, develop models to predict which loans are at risk of default and suggest investment strategies to the client to help them invest in P2P loans with high returns and low risk
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