I’d like to inform that the course has finished and the total of 56 people received a graduation certificate (which required passing homeworks for over 70%), congratulations! 🎉 It was a great experience and I’m happy that I was able to teach so many young students! ...
When working with deep learning problems I usually use PyTorch. I like this framework as it gives me a lot of freedom and allows to write code in the pythonic way. Using bare pytorch unfortunately often means writing a lot of boilerplate code, which no-one like. Another problem that arises during longer and larger projects is experiments running and configuration maintenance. I tackle those two problems by using pytorch-lightning and Hydra. Recently I described my approach in a post on the Appsilon blog. ...
I’m happy to announce that I’ll create and teach the course Python LevelUP: Data Science by Appsilon in collaboration with DaftAcademy, part of DaftCode. This will be a five-week course on the basics of Data Science in python. The course materials will be available on GitHub for free. Apart from teaching the classic stuff, I’ll try to show some of the newest and coolest libraries out there. Even if you already know most of this stuff, I really recommend to take a closer look on the unknown packages. ...
Some time ago, I’ve worked on an oil sac (energy reservoir) detection in copepods (kind of zooplankton) for Université Laval. Apart from presenting the results on the ML4Plankton conference I’ve published a detailed blog post on the Appsilon blog that I strongly encourage you to read! ...
Recently I was working at work on detecting the oil sac in copepods. This is was a super cool problem in which we received data from professor Frédéric Maps from Université Laval. We together gave a talk on conference ML4Plankton that you can watch online! First Frederic gives some context on why this problem is important and later I explain methods used and problems you can find. Our talk is available online here: ...
I wrote another post for Appsilon, this time about deploying streamlit applications on RStudio Connect infrastructure. This post might be totally useless for majority of audience, but a pure gold for a few 💰. What is streamlit you can understand from my previous post. Having a running app in your browser is already cool, but how cool is it to deploy your app on the internet? If you need an enterprise solution for hosting dashboards in RShiny/streamlit, RSConnect is the way! In this blog post I focused on presenting solutions for common problems you might encounter. ...
This one is short. :) Usually when we are doing ML experiments, training models, preparing EDA, we want to share the results with the World at some point. One of the quickest and easiest ways to do so in python, to create a simple webapp with results, is a super-cool library streamlit! If you thought building an app in flask is easy, you will be amazed by streamlit simplicity. Actually you do not have to create an ML related app, nobody checks that ;). ...
As mentioned a month ago, I write a series of posts on detecting solar panels from satellite images at my company, Appsilon. In this post I focus on using fastai python library to deliver a working ML model in few hours! ...
I’m writing a series of posts on detecting solar panels from satellite images at my company, Appsilon. To be honest, not from satellite images but from orthophotos. If you don’t know what are orthophotos, the good news is that the first post has been released recently!. ...
Recently I wrote a post about DVC at my company’s, Appsilon blog. DVC is like a git, but for data, models and experiments. It also allows for creating an automated experiments pipelines. As a teaser I’ll just say that, having prepared scripts for model training and evaluating, when new data is added to the repo, the whole training is run automatically. Metrics are saved to appropriate files alongside with parameters, same with plots. However, if you just upload a new test data, a part of pipeline will be run only. This is a pretty simple case, but DVC is a very powerful tool, check out different use cases in their docs. ...