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

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

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

containing everything about python development and implementations

Dynamic and Static

Impacket is a collection of Python classes for working with network protocols.

Elevate Your Laravel API Development with the API Helper: Build High-Performance APIs with Ease (https://thedigitalmedium.com)

✨ Basic template for run iOS & Android devices simultaneously

Srishty's Brain Child: Goat Cyber Space Inc.

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

Tools & Techniques for Computational Economics

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

Missing Semester 学习总结/核心知识点汇总

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

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

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

This project forecasts hourly taxi demand for peak times using historical data from airports. It uses pandas for data preparation and scikit-learn for building and evaluating predictive models like Random Forest and Gradient Boosting. The project aims to enhance driver availability during rush hours by predicting the number of future taxi orders

This project develops a machine learning model to estimate used car market values for a pricing app. Using pandas for data manipulation and models like Random Forest, Gradient Boosting, and Linear Regression, it aims to balance prediction quality, speed, and training time. It compares multiple models to find the best fit for predicting car prices

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

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