Softlandia
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Posts tagged with
#Data Science
The Rise of Applied AI Engineers and the Shift in AI Skillsets
Discover how the rise of Applied AI Engineers is reshaping the AI development landscape, bridging the gap between cutting-edge AI capabilities and practical, real-world applications for businesses.
Recap of the First Data Science Infrastructure Meetup
The first event focused on the tools and infrastructure that enable productive data science, machine learning and analytics projects.
Recap of the second data science meetup
Our second data science meetup of the year was held on 21.3.2023, and it was great!
Building NLP solutions: strategies and tools
Here we give a roadmap to creating an effective NLP service, and list some of our favourite tools.
Training tiny specialized language models
Here, we're demonstrating a new transformer architecture called MEGABYTE, and training it on a new interesting dataset called TinyStories, on a laptop!
Bridging the AI Gap with Softlandia's Expertise
As AI keeps changing, businesses need to adapt quickly to stay ahead of the competition.
Real-time data processing in Python - technology evaluation
In this blog post, we take a look at stateful stream processing technologies for Python. All code is made available.
Metaflow in Practice
In this blog post, we'll show how to use Metaflow to write production-grade data science workflows.
Distributed Data Science with Metaflow and Dask
In this blog post, we’ll show how to progress with Metaflow when you want to start utilizing the cloud. We’ll use open source software in the Azure cloud to boost our productivity.
Scheduling data science workflows in Azure with Argo and Metaflow
In this blog post, we show how to automate data processing pipelines with Metaflow in Azure using Argo Workflows!
Series of free-of-charge meetups (hybrid) focusing on data science infrastructure - starting 24.1.2023
Learn from the best at our free data science infrastructure event!
Data Science on Azure with Metaflow
Metaflow is an open-source data science framework. How does it compare to Azure's data science tools?