Name: Fadoua Khmaissia
Type: User
Company: University of Louisville
Bio: Machine Learning PhD candidate. Interested in deep learning, learning with limited labeled data, AI for Social Good and AI for Climate Change.
Twitter: fKhmaissia
Location: Louisville, KY
Blog: https://www.linkedin.com/in/fadoua-khmaissia/en
Fadoua Khmaissia's Projects
Opus (transcoding) and VP8 (passthrough) support for Asterisk, needed for a better WebRTC integration
Semi-supervised Deep Learning for Automatic Target Recognition --
Cool links & research papers related to Machine Learning applied to source code (MLonCode)
:scroll: An up-to-date & curated list of awesome semi-supervised learning papers, methods & resources.
PyTorch implementation of Barlow Twins.
Non official implementation of Explanation-based Data Augmentation for Image Classification: https://openreview.net/pdf?id=Ydlco-tfIG
Confidence Guided Generative Data Augmentation for semi-supervised Training
Notebooks for learning deep learning
Python and JavaScript bindings for calling the Earth Engine API.
Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network
Data driven materials discovery
Unofficial PyTorch implementation of "FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence"
Pre-training without Natural Images (ACCV 2020 Best Paper Honorable Mention Award)
Classify and predict reviewers’ sentiments (positive or negative) based on iMDb movies reviews dataset using Python and Keras.
List of interesting articles on different topics of machine learning and deep learning
machine learning and deep learning tutorials, articles and other resources
A machine learning course using Python, Jupyter Notebooks, and OpenML
Deep Metric Transfer for Label Propagation with Limited Annotated Data
Project in MIT COVID-19 Challenge
Code for "MixMatch - A Holistic Approach to Semi-Supervised Learning"
Unofficial pytorch implementation for "MixMatch: A Holistic Approach to Semi-Supervised Learning"
Notes from Coursera specialization: DeepLearning.AI TensorFlow Developer (https://www.coursera.org/professional-certificates/tensorflow-in-practice)
A PyTorch library for benchmarking deep metric learning. It's powerful.
PyTorch implementation of Contrastive Learning methods; List of awesome-contrastive-learning papers
PyTorch implementation of consistency regularization methods for semi-supervised learning
Some custom dataset examples for PyTorch
Deep Learning (with PyTorch)
The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.