An List of my Powershell scripts, commands and Blogs for windows Red Teaming.

• UpdatedFeb 23, 2025
• PowerShell

🗡️ Discover our curated list of creative tools to supercharge your next project.

• UpdatedOct 18, 2024
• CSS

Tool for searching information via Telegram, Number Phone and Username.

• UpdatedJan 31, 2025
• Python

A collection of awesome software, libraries, Learning Tutorials, documents, books, resources and interesting stuff about APIs

• UpdatedJul 4, 2022

Securing LLM's Against Top 10 OWASP Large Language Model Vulnerabilities 2024

• UpdatedMay 10, 2024

Capacità di collegare i dati raccolti da fonti diverse - Ability to link data collected from various sources

• UpdatedDec 12, 2024

containing everything about python development and implementations

• UpdatedNov 13, 2022
• Python

This project focuses on analyzing customer purchasing patterns on Instacart to understand product affinities and shopping behaviors. Data exploration, feature engineering, and collaborative filtering using Python libraries such as pandas and scikit-learn. Helps Instacart optimize product recommendations and improve inventory management

• UpdatedOct 5, 2024
• Jupyter Notebook

This project predicts customer churn for a telecom company by analyzing user contracts, personal data, and service usage. It uses pandas for data manipulation and scikit-learn for model building, applying Logistic Regression, Decision Trees, and Gradient Boosting. The aim is to enable proactive customer retention supporting business decisions

• UpdatedOct 5, 2024
• Jupyter Notebook

Automates the creation of a data science tutorial with machine learning using Serper API and OpenAI. Four agents (Researcher, Writer, Developer, Reviewer) collaborate to research, write, code, and review, resulting in a complete tutorial with code examples. Includes setup instructions for using API keys and environment configuration.

• UpdatedNov 5, 2024
• Python

This project developed a predictive model to estimate additional profits from two loyalty programs at a major retailer. By analyzing growth rates, revenues, and customer behavior, the model distinguished between organic growth and profits driven by loyalty campaigns.

• UpdatedOct 20, 2024

Just a bunch of simple tools/scripts that can help you to have fun while using containers for development on either your local machine or on your own container server

• UpdatedDec 21, 2021
• Shell

This project analyzes a dataset on video game sales to uncover patterns that determine a game's success. The analysis covers user reviews, sales by platform and genre, and regional preferences. Python (pandas, matplotlib) is used for data manipulation and visualization, while various statistical methods explore correlations and trends.

• UpdatedOct 5, 2024
• Jupyter Notebook

This project aims to detect negative movie reviews for the Film Junky Union community by analyzing IMDB data. It uses pandas for data manipulation and scikit-learn for building models, including Logistic Regression and Gradient Boosting. Applies tokenization and TF-IDF are applied to classify reviews as positive or negative

• UpdatedOct 5, 2024
• Jupyter Notebook

✨ Basic template for run iOS & Android devices simultaneously

• UpdatedFeb 1, 2024
• C++

This project developed a model to analyze and track the profitability of contracts at a law firm. It integrated data on revenue, attorney costs, contract expenses, billable hours, and indirect costs to evaluate individual contract performance. The model provided valuable insightslater evolved into a customized system still in use today

• UpdatedOct 20, 2024

This project aims to predict customer insurance claims by analyzing personal data and claim history. Using models like Decision Trees, Random Forests, and Logistic Regression, it evaluates customer risk factors and insurance claim frequency. Data preprocessing and feature engineering are employed, while accuracy and F1-score measure effectiveness

• UpdatedOct 5, 2024
• Jupyter Notebook

PUBLICATION: High-throughput analysis of adaptation using barcoded strains of Saccharomyces cerevisiae

• UpdatedJun 11, 2021
• HTML

This project builds a classification model for Megaline's telecom clients to recommend updated plans based on their usage behavior. It utilizes machine learning algorithms like Decision Trees, Random Forests, and Logistic Regression to maximize accuracy. The goal is to enable plan recommendations, improving customer satisfaction and revenue

• UpdatedOct 5, 2024
• Jupyter Notebook

This project analyzes taxi trip data in Chicago to identify patterns in passenger preferences and the impact of external factors like weather on ride frequency. SQL is used for data extraction, and pandas/scikit-learn are utilized for exploratory data analysis and hypothesis testing. The outcomes improve marketing strategies and user experience

• UpdatedOct 5, 2024
• Jupyter Notebook