Learn about best practices and tools for starting your first deep learning image classification project. This article discusses PyTorch, TensorFlow, fastai, ResNet-50, ResNet-101, MobileNet, and several other concepts and tools.

Defining custom neural network architectures isn't necessary. Learn how to build a 99% accurate image classifier with Transfer Learning and PyTorch.

Convolutional neural networks and deep learning don't have to be difficult subjects. Read this article if topics like input and output channels, kernels, strides, and receptive fields feel a bit fuzzy to you.

Learn best practices for setting up a data science team and kicking off a data analytics project – remote or otherwise. I'll cover Scrum methodology, Asana, GitHub, Docker, renv, linter, and a variety of other tools and workflows.

Unveiling secrets of black box models is no longer a novelty but a new business requirement.

Olga tells her story about being women in the tech industry and her experience on working in Appsilon.

Summary from eRum conference in Budapest. Top talks and video from Olga's talk about new Shiny packages: “Taking inspirations from proven frontend frameworks to add to Shiny with 6 new packages”

Discover who is coming to eRum 2018 in Budapest while playing with an interactive data visualization in D3.js. Vist visualization’s page.

Introduction to R sentiment analysis by analyzing the subtitles of the top 5 romantic comedies - code and charts included!

We find having a Shiny App that allows for Excel export to be a good compromise between R/Shiny and Excel.

Benchmark showing speed of data loading from files by using different methods.

R Viridis color palette with Plotly and Leaflet will make your data visualisations stand out - Here's how to use it.