Hugo RICHARD

Hugo RICHARD

Research Scientist

Sitemap

A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.

Pages

Posts

Future Blog Post

less than 1 minute read

Published:

This post will show up by default. To disable scheduling of future posts, edit config.yml and set future: false.

Blog Post number 4

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 3

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 2

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 1

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

portfolio

Brainiak

Short description of portfolio item number 1

publications

software

talks

teaching

Introduction to Linear Algebra

Undergraduate course, IUT Orsay (2018), 1900

An introduction to linear algebra concluding with an introduction to abstract vector spaces.

Modelisation

Undergraduate course, IUT Orsay (2021), 1900

Linear algebra and coupled first order differential equations

Introduction to machine learning

Graduate course, PSL (2022), 1900

  • Machine learning: recent successes
  • Introduction to machine learning
  • Introduction to Python and Numpy for data sciences.
  • Machine learning models (linear, trees, neural networks).
  • Scikit-learn: estimation/prediction/transformation
  • Practice of Scikit-learn
  • The linear model, optimization
  • Logistic regression with gradient descent
  • Introduction to Deep-Learning
  • Deep learning in practice (Pytorch)

Introduction to machine learning

Graduate course, PSL (2022), 1900

  • Machine learning: recent successes
  • Introduction to machine learning
  • Introduction to Python and Numpy for data sciences.
  • Machine learning models (linear, trees, neural networks).
  • Scikit-learn: estimation/prediction/transformation
  • Practice of Scikit-learn
  • The linear model, optimization
  • Logistic regression with gradient descent
  • Introduction to Deep-Learning
  • Deep learning in practice (Pytorch)