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

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

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

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

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.

Some nlp utils file I write to reuse

A Python package for flexible subset selection for data visualization.

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

Process of data preparaton in R.

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

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

A method for sampling a balanced dataset from biased signals by leveraging statistical distributions derived from the data.

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