arnaudlionellozahic Goto Github PK
Name: Arnaud Lionel Lozahic
Type: User
Location: Paris
Name: Arnaud Lionel Lozahic
Type: User
Location: Paris
We apply a hybrid generational adversarial model for style transfer upon underlying 3D scene structures such as voxel grids and meshes.
This repository is my documenting repository for learning the world of DevOps. I started this journey on the 1st January 2022 and I plan to run to March 31st for a complete 90-day romp on spending an hour a day including weekends to get a foundational knowledge across a lot of different areas that make up DevOps.
DevOps content, classes and exercises
Here is the solved quiz for AI for Everyone course on Coursera
Neural Style Transfer with Caffe2 on your Android phone
Based on tensorflow's style transfer Android project.
An Android app built with an artistic style transfer neural network
A very neat and simple starter kit for an angular2/4/5 MEAN app.
:iphone: Automation for iOS, Android, and Windows Apps.
A curated list for DevOps learning resources. Join the slack channel to discuss more.
A collection of handy Bash One-Liners and terminal tricks for data processing and Linux system maintenance.
The Rust Programming Language
Materials for "How to Win a Data Science Competition: Learn from Top Kagglers" course
Udemy - Linux Academy - AWS Essentials
✅ Solutions to MachineLearning, DeepLearning, NeuralNetwork
Quiz & Assignment of Coursera
Docker container with Jupyter Environment for Coursera "Advanced Machine Learning" specialization.
Homework from the deeplearning.ai Deep Learning Specialization on Coursera
Coursera's Machine Learning by Andrew Ng
About this Course If you want to break into cutting-edge AI, this course will help you do so. Deep learning engineers are highly sought after, and mastering deep learning will give you numerous new career opportunities. Deep learning is also a new "superpower" that will let you build AI systems that just weren't possible a few years ago. In this course, you will learn the foundations of deep learning. When you finish this class, you will: - Understand the major technology trends driving Deep Learning - Be able to build, train and apply fully connected deep neural networks - Know how to implement efficient (vectorized) neural networks - Understand the key parameters in a neural network's architecture This course also teaches you how Deep Learning actually works, rather than presenting only a cursory or surface-level description. So after completing it, you will be able to apply deep learning to a your own applications. If you are looking for a job in AI, after this course you will also be able to answer basic interview questions. This is the first course of the Deep Learning Specialization.
Jupyter_Notebook solutions for the deep learning course on Coursera
daru-view is for easy and interactive plotting in web application & IRuby notebook. daru-view is a plugin gem to the existing daru gem.
Data Science Repo and blog for John Hopkins Coursera Courses. Please let me know if you have any questions.
Machine learning datasets used in tutorials on MachineLearningMastery.com
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.