dcleres,David Cleres,DavidCleres,github

awesome-profile-readme-templates

A collection of awesome readme templates to display on your profile

backstage

Backstage is an open platform for building developer portals

bio-465-biological_modeling_of_neural_networks

Notebook with the projects performed for the class of Biological modeling of neural networks @EPFL

brc-draft-documentation

A place to contribute edits to documentation for Berkeley Research Computing services (e.g. the Savio HPC cluster, Cloud Consulting Support)

cs-433-machinelearning

Repository of the Projects performed for the EPFL Machine Learning course (CS-433)

deepshape

Deep learning on 3d meshes via model simplification

Competition Description MNIST ("Modified National Institute of Standards and Technology") is the de facto “hello world” dataset of computer vision. Since its release in 1999, this classic dataset of handwritten images has served as the basis for benchmarking classification algorithms. As new machine learning techniques emerge, MNIST remains a reliable resource for researchers and learners alike. In this competition, your goal is to correctly identify digits from a dataset of tens of thousands of handwritten images. We’ve curated a set of tutorial-style kernels which cover everything from regression to neural networks. We encourage you to experiment with different algorithms to learn first-hand what works well and how techniques compare. Practice Skills Computer vision fundamentals including simple neural networks Classification methods such as SVM and K-nearest neighbors

douzero

[ICML 2021] DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement Learning | 斗地主AI

dvc

🦉Data Version Control | Git for Data & Models | ML Experiments Management

flirt

Are you ready to FLIRT with your wearable data?

hatschi-backend

A backend for an app like Hatschi that allows you to track the cough data of multiple patients.

iampoorapp

Simple iOS app that displays a rock and the "I am poor" text

investing_for_social_good

“data science for social good”, Think about how you could improve society through data analysis!

io

Dataset, streaming, and file system extensions maintained by TensorFlow SIG-IO

joj

Think about all of the food you have eaten during the last year. Do you know for a fact if it was healthy or good for you? We believe that you could do much better, and we have a solution! Regain control on what you eat, and become healthy again! With Qeeqbii, eating healthy is not a concern anymore. The app will warn you if you’re getting a risk eating the food that you are daily buying and alerting you when the contents of your fridge do not constitute a healthy diet. Everybody’s different, and Qeeqbii knows it: the app will give specific advices, based on all the aspects of your profile. Eat healthy again, and you’ll gain the energy to get over every challenge life puts on your path. The app will instantly display the amount of important constituents the products you have bought contain. For example, after you scan a can of coke, an yoghurt and a pack of spaghetti, you will now know if your shopping list meets the daily requirements on proteins, salt, sugar, fat and energy. Moreover, the app will alert you if your ration is not balanced. For example, if you eat frozen pizza often, you might lack certain elements which are contained in fruits. The app will display a message and suggest you to buy some. It will advise you to eat in a healthy way without you ever thinking about it. Finally, the app tracks every product in the fridge you have. Each time you go to a supermarket and have a list of products to buy, you will be able to compare it to what you have in the fridge so you wouldn’t forget to buy that pasta you finished the day before! Moreover, you will be able to automatically check the item on your shopping list the moment you scan the barcode.

keras_cv_attention_models

Keras/Tensorflow attention models including beit,botnet,CMT,CoaT,CoAtNet,convnext,cotnet,efficientdet,efficientnet,gmlp,halonet,levit,mlp-mixer,nfnets,regnet,resmlp,resnest,resnext,resnetd,volo,yolox

libigl-example-project

A blank project example showing how to use libigl and cmake.

ml_course

EPFL Machine Learning Course, Fall 2017

osrm-backend

Open Source Routing Machine - C++ backend

parkinson_disease_ml

A comparative analysis of speech signal processing algorithms for Parkinson’s disease classification and the use of the tunable Q-factor wavelet transform