Loan Eligibility Prediction Model: A machine learning application to predict loan approval based on applicant data. Includes a web interface for submitting loan applications and receiving predictions. Built with Python and Jupyter Notebook.

This is a simple web based application to predict diabetes.

2023년 11월 대한산업공학회(UNIST) : 다중 역할 경험을 고려한 게임 유저 이탈 예측: 롤 게임을 중심으로, 1저자

Flexible HDF5 saving/loading and other data science tools from the University of Chicago

in this project we will train models and use them to auto completing texts in persian.

This Mediawiki extension adds Pickle testing of Lua modules. An integral part is to report failures clearly and visible to facilitate interactive and collaborative fault fixing.

A GDB+GEF-style debugger for unloading Python pickles

Python library for serializing any arbitrary object graph into JSON. It can take almost any Python object and turn the object into JSON. Additionally, it can reconstitute the object back into Python.

EDA, visualizations and model training were done over the Heart Disease Dataset. Web app was made using HTML, CSS and Flask, which allows user to enter their medical info and check the risk of heart disease. A KNN model was deployed into the web-app using Python's Pickle module to make the risk prediction based on medical into entered by user.

Movie Review Sentiment offers a robust backend solution for sentiment analysis of movie reviews, employing Flask and machine learning to classify review sentiments in real-time.

Software built using Python which makes use of CNN and FNN to detect the Taals of the Tabla, an Indian classical music instrument.

We are proud to introduce our new book recommendation system, book.io. This system uses the user-to-user collaborative filtering model to recommend books to users based on their preferences and ratings.

🏡 House Price Prediction with Machine Learning Project 🤖💰 Seeking to revolutionize the real estate industry with cutting-edge technology? Explore my latest project, where I leveraged machine learning algorithms to predict house prices accurately.

Rating: (8/10) The project uses natural language processing to create a chatbot capable of understanding user queries. It trains on a dataset of intents, tokenizing patterns, and constructing a neural network model. The model is saved for future use.

Aplicação web onde você consegue treinar um modelo de Machine Learning para classificar uma pessoa como do sexo masculino ou feminino com base em seu nome.

📘 dict subclass with keylist/keypath support, built-in I/O operations (base64, csv, html, ini, json, pickle, plist, query-string, toml, xls, xml, yaml), s3 support and many utilities.

🍀🤖 Демонстрационной квиз-бот для ICQ New

An experimental tool to find fastest winning moves using bruteforce for the board game Splendor

A Gherkin/Pickle linter written in javascript

A simple immutable dictionary for Python