Data and tools for generating and inspecting OLMo pre-training data.

SDN networks (Software Defined Networking ) are exposed to new security threats and attacks, especially Distributed Denial of Service (DDoS) attacks. For this aim, we have proposed a model able to detect and mitigate attacks automatically in SDN networks using Machine Learning (ML)

How to improve a 14% your image matching with only one line of code? BEBLID is the key!

A Hand Written Digit Recognition app trained on the MNIST dataset of Keras using the CNN model. skills used are Tensorflow, HTML,CSS,javascript.

Front end for Heart Disease Analysis and Prediction Project

Proyecto de entrenamiento de modelos de IA con aprendizaje por refuerzo (reinforcement learning) en Unity. Corresponde al trabajo práctico grupal de la materia INTELIGENCIA ARTIFICIAL (9525) de la Facultad de Ingeniería de la Universidad de Buenos Aires. Link a la demo (el comportamiento de los agentes puede verse afectado de forma negativa):

MLP Regression model to predict quantitative data

Stroke-GFCN: segmentation of Ischemic brain lesions

💻 Personal blog/website, built using Jekyll & Github pages.

Clone your favorite voice for your script

SMOTE-MR: A distributed Synthetic Minority Oversampling Technique (SMOTE) for Big Data which applies a MapReduce based-approach. SMOTE-MR is categorized as an `approximated/ non exact` solution. Also, there is an `exact` solution called SMOTE-BD written by the author (See: https://github.com/majobasgall/smote-bd)

Master's program ''Machine learning and high-load networks'' at the Higher School of Economics.

Kaggle Competition...

Real-Estate Price Predictor is a machine learning project developed to assist users in estimating the price of real estate properties based on various features such as location, size, amenities, etc. The project utilizes supervised learning algorithms to train models on historical real-estate data and predicts prices for new properties.

Implementação de algoritmos de aprendizado de máquina para detecção de doença em radiografias.

This project focuses on detecting Diabetic Retinopathy (DR) from retinal images using machine learning models. The goal is to classify images based on the severity of DR using deep learning techniques. This project uses models like ResNewt50, VGG16, InceptionV3.

Self-driving toy car built in C++ with raspberry pi, opencv, and tensorflow.

Toxic comment classification with Flask API

machine learning for design

A program made using DeepAI and python for smart refrigerator for HackWithInfy Hackathon