Jupyter Notebooks and Quarto 📓📃

2022-09-13

What if you just don’t like rmd/qmd format anymore? You love jupyter notebooks and that’s your way of working (that’s me). Still, you must generate report from time to time. Fortunately quarto solves this problem brilliantly!

The reports look beautifully. Not only htmls what we might expect, but pdfs as well!

I wrote a post for Appsilon that has been published on medium regarding this topic. Be sure to check it out, it was a real game-changer for me!

Quarto, Python, and VSCode 📃🐍

2022-08-25

#appsilon #python #quarto

Working with quarto files in RStudio is probably the suggested way. However, you may prefer to use VS Code. Especially if you work mainly in python. It’s not a problem by any means!

I wrote a post on medium on working with quarto in VS Code on python files.

Quarto, The New Rmarkdown 📃📜

2022-07-28

#r #python #quarto

Do you remember good old rmarkdown?

---
title: "R markdown"
output: html_document
---

Hello ~world~ problems!

We have a great successor in the form of quarto that is ready for 2022 and beyond!

PyTorch Serialization 📦⚙️

2022-07-07

#appsilon #python #pytorch #machine-learning

One thing is to train the model, but another is to serve it. In between those two phases, model serialization and deserialization occurs. In simpler words it’s just model saving and loading. It’s important because different methods result in different:

Inference speed
Model size
Python environment size

If you are curious what are the ways to serialize model in PyTorch and how they compare, checkout my new post on Appsilon blog.

DaftAcademy Course Finished 🐍🏁

2022-06-19

#course #python #data science #appsilon #daftacademy

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!

PyTorch-Lightning + Hydra to Boost Your PyTorch ⚡🐉

2022-06-09

#appsilon #python #pytorch #machine-learning

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.

DaftAcademy Announcement 🐍👨‍🏫

2022-04-30

#course #python #data science #appsilon #daftacademy

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.

StyleGANv2 in Your Hands 💇👻

2022-03-14

#python #machine-learning #conference #SFI 2022

This is the second post from micro-series preceding the SFI conference. In the first post I showed how easy it is to do the style transfer at home. Now, I would like to present you how to play with StyleGANv2. StyleGANv2 is the second version of StyleGAN, they are very similar in core principals. We will be working with StyleGANv2 but I will refer to it as SG. There is a lot that can be said/explained about SG.

Streamlit Tutorial: How to Deploy Streamlit Apps on RStudio Connect 💰

2022-02-28

#machine-learning #streamlit #python #R #appsilon

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!

Playing With Style Transfer 🎨

2022-02-05

#python #machine-learning #conference #SFI 2022

As mentioned earlier, I will be giving a talk on the 17th SFI IT Academic Festival on the topic of style transfer and StyleGAN. In this post I would like to show you how easy it is to play with style transfer on your own! To tutorial or not to tutorial # It might be obvious for you to check Tensorflow/PyTorch tutorials if you wanted to learn how to create style-transfer system.

Detecting Solar Panels from satellite images part 3 - PoC model deployment in streamlit 🎈

2022-01-14

#machine-learning #streamlit #python #appsilon

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 ;).

Detecting Solar Panels from satellite images part 2 – machine learning in fastai 🤖

2021-11-29

#machine-learning #python #appsilon

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!

Detecting Solar Panels from satellite images part 1 – data preparation🛰️

2021-11-02

#machine-learning #python #appsilon

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!.

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