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Hi, I'm Seb

I'm an AI and Cloud engineer!

I've been a programmer for many years. I have worked on a wide range of projects throughout my career.

  • 2016: I started with mobile application (iOS and Android) and websites.
  • 2018: I started designing and building cloud infrastructure and creating both frontend and backend solutions.
  • 2020: Over time, my passion for innovation and cutting-edge technology has led me to explore the exciting field of AI and robotics at Samsung Strategy and Innovation Center.
  • 2021-Now: I joined a startup to create a new vision system based on lasers and event-based sensors.

🔭 I'm currently working on AI and DevOps for a robotics startup in the autonomous vehicle space.

🌱 I’m currently learning modern C++ and Graph Neural Networks.

GitHub Stats

Seb's github stats Top Langs

My Stack

Languages:

Python C++ Javascript Typescript

AI and Data:

PyTorch Nvidia Arm

DevOps:

Docker Kubernetes AWS Lambda S3

Full-Stack Application:

ReactJS CSS3 HTML5 NodeJS Express MongoDB

UX/UI:

Figma Miro Adobe Photoshop

Utilities:

VSCode Postman

Business:

Notion Trello Slack

Sébastien Mascha's Projects

blockchain-trufflesuite icon blockchain-trufflesuite

A world class development environment, testing framework and asset pipeline for blockchains using the Ethereum Virtual Machine (EVM), aiming to make life as a developer easier. Everything you need to start using smart contracts from a react app with Drizzle.

camp icon camp

🏕 IPFS Camp is a 3 day hacker retreat designed for the builders of the Distributed Web.

carla icon carla

Open-source simulator for autonomous driving research.

cirq icon cirq

A python framework for creating, editing, and invoking Noisy Intermediate Scale Quantum (NISQ) circuits.

data-science-aws-sagemaker icon data-science-aws-sagemaker

Example notebooks that show how to apply machine learning, deep learning and reinforcement learning in Amazon SageMaker

data-science-dcgan-keras-mnist icon data-science-dcgan-keras-mnist

Generative Adversarial Networks (GANs) are one of the most interesting ideas in computer science today. Two models are trained simultaneously by an adversarial process. A generator ("the artist") learns to create images that look real, while a discriminator ("the art critic") learns to tell real images apart from fakes.

data-science-inference-keras-tensorflow-flask icon data-science-inference-keras-tensorflow-flask

Deploy a Pre-trained TensorFlow model with the help of TensorFlow Serving with Docker, and we will also create a visual web interface using Flask web framework which will serve to get predictions from the served TensorFlow model and help end-users to consume through API calls.

data-science-ml-matlab-andrewng icon data-science-ml-matlab-andrewng

This is a repository of my coursera Machine Learning by Standford, Andrew NG course's assignments, which contains a large collection of algorithms. I implemented these algorithms during Andrew NG's courses. Furthermore, there are hands-on tricks and techniques useful in ML / DL.

data-science-ml-python-isep icon data-science-ml-python-isep

ML and DL repository, which contains a large collection of algorithms in python. I implemented these algorithms during M. SUBLIME's courses.

deepfashion2 icon deepfashion2

DeepFashion2 Dataset https://arxiv.org/pdf/1901.07973.pdf

devops-kubernetes-microservices icon devops-kubernetes-microservices

Guide to Orchestrating Containers. Running a Microservice based application on your computer. Building container images for each service of the Microservice application. Deploying a Microservice based application into a Kubernetes Managed Cluster.

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