The post Unraveling Spatially Variable Genes: A Statistical Perspective on Spatial Transcriptomics appeared first on Towards Data Science.
Reinforcement Learning with PDEs
Previously we discussed applying reinforcement learning to Ordinary Differential Equations (ODEs) by integrating ODEs within gymnasium. ODEs are a powerful tool that can describe a wide range of systems but are limited to a single variable. Partial Differential Equations (PDEs) are differential equations involving derivatives of multiple variables that can cover a far broader range […]
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The post Reinforcement Learning with PDEs appeared first on Towards Data Science.
How to Use an LLM-Powered Boilerplate for Building Your Own Node.js API
For a long time, one of the common ways to start new Node.js projects was using boilerplate templates. These templates help developers reuse familiar code structures and implement standard features, such as access to cloud file storage. With the latest developments in LLM, project boilerplates appear to be more useful than ever. Building on this […]
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The post How to Use an LLM-Powered Boilerplate for Building Your Own Node.js API appeared first on Towards Data Science.
Don’t Let Conda Eat Your Hard Drive
If you’re an Anaconda user, you know that conda environments help you manage package dependencies, avoid compatibility conflicts, and share your projects with others. Unfortunately, they can also take over your computer’s hard drive. I write lots of computer tutorials and to keep them organized, each has a dedicated folder structure complete with a conda environment. This […]
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The post Don’t Let Conda Eat Your Hard Drive appeared first on Towards Data Science.
AI Agents from Zero to Hero – Part 1
Intro AI Agents are autonomous programs that perform tasks, make decisions, and communicate with others. Normally, they use a set of tools to help complete tasks. In GenAI applications, these Agents process sequential reasoning and can use external tools (like web searches or database queries) when the LLM knowledge isn’t enough. Unlike a basic chatbot, […]
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The post AI Agents from Zero to Hero – Part 1 appeared first on Towards Data Science.
Why Data Scientists Should Care about Containers — and Stand Out with This Knowledge
“I train models, analyze data and create dashboards — why should I care about containers?” Many people who are new to the world of data science ask themselves this question. But imagine you have trained a model that runs perfectly on your laptop. However, error messages keep popping up in the cloud when others access […]
The post Why Data Scientists Should Care about Containers — and Stand Out with This Knowledge appeared first on Towards Data Science.
The post Why Data Scientists Should Care about Containers — and Stand Out with This Knowledge appeared first on Towards Data Science.
Advanced Time Intelligence in DAX with Performance in Mind
We all know the usual Time Intelligence function based on years, quarters, months, and days. But sometimes, we need to perform more exotic timer intelligence calculations. But we should not forget to consider performance while programming the measures. Introduction There are many DAX functions in Power BI for Time Intelligence Measures. The most common are: You […]
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The post Advanced Time Intelligence in DAX with Performance in Mind appeared first on Towards Data Science.
Multimodal Search Engine Agents Powered by BLIP-2 and Gemini
This post was co-authored with Rafael Guedes. Introduction Traditional models can only process a single type of data, such as text, images, or tabular data. Multimodality is a trending concept in the AI research community, referring to a model’s ability to learn from multiple types of data simultaneously. This new technology (not really new, but […]
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The post Multimodal Search Engine Agents Powered by BLIP-2 and Gemini appeared first on Towards Data Science.
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