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Author here!

It's a simple example but I was delighted to see how clean the code looked when implemented with outlines so I wanted to share it.

Feel free to ask questions!


Author here!

It's a simple example but I was delighted to see how clean the code looked when implemented with outlines so I wanted to share it.

Feel free to ask questions!


  Location: France, CEST timezone (UTC +2)
  Remote: Yes
  Willing to relocate: No
  Technologies: Python, CUDA, pytorch/JAX/TF, Aws/Docker/Linux, typescript/React
  Résumé/CV: https://morgangiraud.com/public/cv-morgan-giraud.pdf
  Email: contact[AT]morgangiraud[DOT]com
I'm really passionate about ML, both in terms of research and production. I've also founded (as the tech) a startup which operated successfully ~10 years. I'm efficient at understanding product and user experience requirements and distill them into actionable technology, as well as interpreting research papers to enhance models in production.


ML engineer. 10+ years of experience in dev in general and 6 years of experience in ML. Past experiences include: - CTO & cofounder (webapp) (2012 - 2016) - Freelancer (Web/ML) (2016 - 2022) - Code instructor (1 semester) - ML research internship (1 semester) - Lead Developer (2022-2023)

More ML/Web projects at https://morgangiraud.com

Location: Annecy, France Remote: yes (hybrid) Willing to relocate: Maybe Technologies: Python, Pytorch/jax, Typescript, docker Résumé/CV: https://morgangiraud.com/public/cv-morgan-giraud.pdf Email: contact@morgangiraud.com


Quite nice!

> How to speak to insufferable people?

When faced with insufferable people, it's important to focus on yourself and your own conduct. As Seneca said, "It is your conduct that you must hold in check; you must rouse what is languid in you, bind fast what has become relaxed, conquer what is obstinate, persecute your appetites, and the appetites of mankind, as much as you can".

You should also close your ears against evil talk and avoid being drawn into conversations that could lead you astray. As Seneca said, "Virtue, Philosophy, Justice this is a jargon of empty words. The only way to be happy is to do yourself well. To eat, drink, and spend your money is the only real life, the only way to remind yourself that you are mortal"


Understanding itself.


I don't disagree with this, but it might only be a partial answer.


TL, DR:

- I list all the different tasks one will have to do when doing ML

- I show a common folder structure that I believe handles all possible use cases nicely

- I show a basic Model class, easily extendable that structure a lot of possible kinds of models

- I describe how to build a good "shell API" for easy iterations.

Bonus: Some TF code linked to the subject.


TL,DR:

- I explore the different ways to manually mutate Variables in TF (content and shape)

- I explore how to construct control flow like an "if statement"

- I end up and showing a weird TF behaviour when you mix those

- Bonus: a first try at animated GIF :D


You're right, i've been myself using git, github, keynote, ffmpeg, medium, JS, python, d3 and others to build blog post.

I clearly don't expect people to do that much. I can only do that because i'm coming from web development, and very nice tools started to appear recently.

People in research needs a design framework like a set of templates for keynotes/PPT/JS/CSS (think about how much traction got bootstrap). Distill is doing an awesome jobs at showing the example of what you could do.

Maybe Distill could open-source the templates they use to build those blog post?


They did actually! [0] The blog posts are also online on their GitHub site.

[0] https://github.com/distillpub/template


Awesome!


If anybody interested: i've been learning it and wrote some blog posts about it:

https://blog.metaflow.fr/tensorflow-a-primer-4b3fa0978be3#.2...

I hope it can be useful for future learners! (you can find the current list of articles at the end of the first one)


That is a very helpful primer. What resources did you use to learn that level of understanding in TensorFlow? Just the codebase? If you have any other articles or references to recommend, please do so. Thanks!


Thanks for this feedback!

I've just spent some time learning TF on my own using the official doc and made a lot of projects on my Githubs.

If you're interested, here is the complete list of my articles so far:

How to handle shapes in TensorFlow: https://blog.metaflow.fr/shapes-and-dynamic-dimensions-in-te...

TensorFlow saving/restoring and mixing multiple models: https://medium.com/@morgangiraud/tensorflow-saving-restoring...

How to freeze a model and serve it with a python API: https://blog.metaflow.fr/tensorflow-how-to-freeze-a-model-an...

TensorFlow howto: a universal approximator inside a neural net: https://blog.metaflow.fr/tensorflow-howto-a-universal-approx...

How to optimise your input pipeline with queues and multi-threading: https://blog.metaflow.fr/tensorflow-how-to-optimise-your-inp...


wow... Thanks for these links. I find the offical docs of TF are atrocious and I have a lot of trouble figuring it out.


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