A (PyTorch) imbalanced dataset sampler for oversampling low frequent classes and undersampling high frequent ones.

Microarchitectural exploitation and other hardware attacks.

State-of-the-art neural cardinality estimators for join queries

TIP2022 Adaptive Boosting (AdaBoost) for Domain Adaptation ? 🤷‍♀️ Why not ! 🙆‍♀️

Reinforced Data Sampling

This project aims to analyze the citation network of arXiv papers. We use Python to clean the data and create a Neo4j network to visualize and analyze the citation relationships between arXiv papers.

Implémentation d'un modèle de scoring (OpenClassrooms | Data Scientist | Projet 7)

This file covers all concepts of R language..

Generating realistic test data or simulating load with authentic, dynamic data using the Gatling framework and JavaFaker

BiBiER: A Bilingual Bimodal Emotion Recognition Method with Improved Generalization through Data Augmentation

Adaptive data sampling and transmission in a wireless sensor node as a function of energy reserves

Dynamic cluster-based data sampling for efficient and long-tail-aware vision-language model pre-training.

Fraud detection in credit cards using Random Forest & strategic sampling | Detecção de fraudes em cartões de crédito com Random Forest e amostragem estratégica.

Process of data preparaton in R.

This repository contains experiments on data wrangling techniques, focusing on methods for handling missing values, filtering, aggregation, and more.

A Python package for flexible subset selection for data visualization.

Some nlp utils file I write to reuse

Here is Task 5: Credit card fraud detection using machine learning, for my data science internship with Codsoft

Professional Python tool for intelligently selecting and copying media files with advanced filtering, performance optimization, and resume capabilities. Perfect for dataset creation, content curation, and large-scale media management.

Code and Data for paper: Variation across Scales: Measurement Fidelity under Twitter Data Sampling (ICWSM '20)