glemaitre Goto Github PK
Name: Guillaume Lemaitre
Type: User
Company: Open-source engineer @probabl-ai
Twitter: glemaitre58
Location: Paris-Saclay / France
Name: Guillaume Lemaitre
Type: User
Company: Open-source engineer @probabl-ai
Twitter: glemaitre58
Location: Paris-Saclay / France
ACME - Accelerated Model Explainability
Project management related documents for scikit-learn
Air passengers RAMP starting kit
Small project to explore different types of amputation
Approximate Nearest Neighbors in C++/Python optimized for memory usage and loading/saving to disk
Site internet de l'ASC Fours
RAMP on Autism Spectrum Disorder detection
Continuous integration for a basic Node.js project with Shippable https://www.shippable.com
Beamer for LE2I
Bike counters RAMP starting kit
Hosting the scikit-learn blog.
Clone from http://www.cs.tut.fi/~foi/GCF-BM3D/index.html#ref_software
Boston housing price regression
brew: Python Ensemble Learning API
c-lasso: a Python package for constrained sparse regression and classification
Prostate cancer is the second most diagnosed cancer of men all over the world. In the last few decades, new imaging techniques based on Magnetic Resonance Imaging (MRI) have been developed to improve diagnosis. In practise, diagnosis can be affected by multiple factors such as observer variability and visibility and complexity of the lesions. In this regard, computer-aided detection and computer-aided diagnosis systems have been designed to help radiologists in their clinical practice. Research on computer-aided systems specifically focused for prostate cancer is a young technology and has been part of a dynamic field of research for the last 10 years. This survey aims to provide a comprehensive review of the state-of-the-art in this lapse of time, focusing on the different stages composing the work-flow of a computer-aided system. We also provide a comparison between studies and a discussion about the potential avenues for future research. In addition, this paper presents a new public online dataset which is made available to the research community with the aim of providing a common evaluation framework to overcome some of the current limitations identified in this survey.
Tutorial on probablistic classification and cost-sensitive learning.
Analyzing fMRI and behavioral data from Cam-CAN dataset.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.