Командный репозиторий.

a tool for comparing the predictions of any text classifiers

🌟 This repository is related to the projects related to 🤖🧠💻 Artificial Intelligence, Machine Learning and Data Science given by PWSKILLS for the course "DATA SCIENCE MASTERS - IMPACT BATCH 1" 🚀

mltrons dptron: Dirty Data in, Clean Data Out!

All FreeCodeCamp Certification with Projects

🔍 Discover the future of healthcare with our Lung Cancer Detection Project. Using advanced machine learning techniques, we've achieved 92% accuracy in identifying lung cancer. Join us at the forefront of medical AI. 👩‍⚕️🌟 #AIHealthcare #LungCancerDetection

A Lesson and an interactive Tool for learning Artificial Neural Networks. (Implementation of Forward/Backprop algorithm using numpy)

Marketing prediction models using Starbucks app member data sets. Regression models to predict profitability of promotional campaign configurations using KNN, Linear Regression, Mini-batch Gradient Descent, and Neural Network.

language model for basic jack and jill poem using RNN

This is a web app where you can draw a letter in the russian alphabet and the ML algorithm will predict the letter that you drew.

A Multi Document Summarizer Using Bidirectional Encoder Representations from Transformers (BERT)

A Lesson & implementation of Decision Tree Classifier in Numpy and Python

Environmental Data Management Toolbox

A university project consisting of a data mining phase and the development of a web application that allows the user to classify a specific emotion using the James Russel valence-arousal domain.

A front end dashboard for a credit scoring app, deployed on Heroku inside a Docker container. The backend is a REST API server using a custom ML model.

Data Science Course Project 2024 - UNIVERSITAS MARITIM RAJA ALI HAJI FAKULTAS TEKNIK DAN TEKNOLOGI KEMARITIMAN PROGRAM STUDI TEKNIK INFORMATIKA

DisasterResponseAI: Crisis management with NLP-powered message classification for swift, targeted relief efforts. #DataScience #MachineLearning #EmergencyResponse

Telecom Customer Churn Prediction This repository contains a machine learning project focused on predicting customer churn in the telecommunications industry. By leveraging a dataset of customer demographics and usage patterns, we develop and deploy a predictive model to identify customers at risk of leaving the service.

A credit score API REST server using a custom ML model documented using Swagger and deployed on HEROKU.