2023-07-24
#conference
#OxML
#Oxford
#machine-learning
#appsilon The report of all talks during the fourth day of OxML Health 2023 where I’ve been on behalf of Appsilon..
This day talks were on:
- Insightful Lecture on ML for Mental Health - Munmun De Chodhury
- Drug Discovery with ML - Ravi Patel
- How to make sure the Market wants your solution - Reza Khorshidi
2023-07-23
#conference
#OxML
#Oxford
#machine-learning
#appsilon The report of all talks during the third day of OxML Health 2023 where I’ve been on behalf of Appsilon..
This day talks were on:
- Introduction to Neural Networks - Gitta Kutyniok
- Medical Expert’s View on Impactful and Responsible ML in Health with EHR - Kazem Rahimi
- Chaotic Lecture on Graphs and ML - Pietro Liรฒ
2023-07-22
#conference
#OxML
#Oxford
#machine-learning
#appsilon The report of all talks during the second day of OxML Health 2023 where I’ve been on behalf of Appsilon..
This day talks were on:
- The State of Computer Vision and Many CV Experiments - Cristian Rupprecht
- ML Challenges in Oncology and Multi-omics data - Mireira Crispin
- What is a Multimodality and How To Work With It? - Louis-Philippe (LP) Morency
2023-07-21
#conference
#OxML
#Oxford
#machine-learning
#appsilon The report of all talks during the first day of OxML Health 2023 where I’ve been on behalf of Appsilon.
This day talks were on:
- Casual Inference - Cheng Zhang
- Computer Vision in medicine - Jorge Cardoso
- Knowledge Representation - Ali Eslami
2023-07-20
#conference
#OxML
#Oxford
#machine-learning
#appsilon Long time no see ^^
Today, I’d like to share my experience from OxML Health Summer School that I attended in person this year on behalf of Appsilon.
2022-10-01
#data4good
#machine-learning
#appsilon It’s always nice if you can use your technical skills for something good for our planet.
I have this opportunity during work at Appsilon where from time to time we work on Data4Good projects.
One such project was copepods/plankton project where I was doing segmentation of the oil sac in the Arctic plankton.
This time I’d like to share something from the other pole of the globe.
Currently we work on detecting the Antarctic shags nests on the Antarctic islands.
Together with Jฤdrzej ลwieลผewski and Joanna Kaleta we were cooperating with researchers from IBB PAS on this task.
Checkout the engagement summary blog post on the Appsilon blog.
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.
2022-07-01
#conference
#SFI 2022
#machine-learning Finally the recording of the talk StyleGAN w Twoich rฤkach from SFI 2022 is available online! ๐
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.
2022-04-15
#appsilon
#data4good
#machine-learning Some time ago, I’ve worked on an oil sac (energy reservoir) detection in copepods (kind of zooplankton) for Universitรฉ 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!
2022-04-08
#appsilon
#data4good
#conference
#machine-learning 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 Frรฉdรฉric Maps from Universitรฉ 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:
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.
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 ๐ฐ. 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!
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.
2022-01-20
#conference
#SFI 2022
#machine-learning I am happy to share that I was invited (for the first time in my life!) to give a talk on a conference. ๐ It will be the 17th SFI IT Academic Festival, organized by students from the Jagiellonian University in Cracow. The conference will be held on 14-16 of March 2022.
My lecture will be in Polish on topic StyleGAN w Twoich rฤkach -> StyleGAN in Your Hands, I will talk about transfer learning in general and later about StyleGANv2.
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 ;).
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!
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!.
2021-10-13
#machine-learning
#dvc
#appsilon 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.