The Power of Framework Dimensions: What Data Scientists Should Know
A previous article provided a of conceptual frameworks – analytical structures for representing abstract concepts and organizing data. Data scientists ...
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Building a Geospatial Lakehouse with Open Source and Databricks
Most data that relates to a measurable process in the real world has a geospatial aspect to it. Organisations that ...
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How to Control a Robot with Python
PyBullet is an open-source simulation platform created by Facebook that’s designed for training physical agents (such as robots) in a ...
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Why Should We Bother with Quantum Computing in ML?
When black cats prowl and pumpkins gleam, may luck be yours on Halloween. (Unknown) , conferences, workshops, articles, and books ...
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Scaling Recommender Transformers to a Billion Parameters
! My name is Kirill Khrylchenko, and I lead the RecSys R&D team at Yandex. One of our goals is ...
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How to Build An AI Agent with Function Calling and GPT-5
and Large Language Models (LLMs) Large language models (LLMs) are advanced AI systems built on deep neural network such as transformers ...
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Conceptual Frameworks for Data Science Projects
are analytical structures for representing abstract concepts and organizing data. Data scientists regularly use such frameworks — knowingly or unknowingly ...
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Learning Triton One Kernel at a Time: Matrix Multiplication
multiplication is undoubtedly the most common operation performed by GPUs. It is the fundamental building block of linear algebra and ...
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How To Build Effective Technical Guardrails for AI Applications
with a bit of control and assurance of security. Guardrails provide that for AI applications. But how can those be ...
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Dreaming in Blocks — MineWorld, the Minecraft World Model
Mineworld gameplay, taken from the GitHub repository [4], licensed under the MIT License. games growing up was definitely Minecraft. To ...
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