5 Useful Python Scripts for Automated Data Quality Checks
Bad data leads to bad decisions. These Python scripts will help you catch data quality issues before they cause problems.
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February 2026
Take a Deep Dive into Filtering in DAX
Have you ever wondered what happens when you apply a filter in a DAX expression? Well, Today I will take you on a deep dive into this fascinating topic, with examples to help you learn something new and surprising. The post Take a Deep Dive into Filtering in DAX appeared first on Towards Data Science.
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Detecting and Editing Visual Objects with Gemini
A practical guide to identifying, restoring, and transforming elements within your images The post Detecting and Editing Visual Objects with Gemini appeared first on Towards Data Science.
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A Generalizable MARL-LP Approach for Scheduling in Logistics
Part 1. Hybrid Solution for Dynamic Vehicle Routing — Context and Architecture The post A Generalizable MARL-LP Approach for Scheduling in Logistics appeared first on Towards Data Science.
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Designing Data and AI Systems That Hold Up in Production
A system-level perspective on architecture, agents, and responsible scale The post Designing Data and AI Systems That Hold Up in Production appeared first on Towards Data Science.
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Outtelligence: The Advantage AI Cannot Compound
I’m going to introduce a new word. Not because the idea is new. But because the moment demands a name for it. The word is Outtelligence. And if artificial intelligence continues accelerating the way it is, this may become the most important cognitive skill of the next decade. If you study capital markets long enough, you learn something simple: When something becomes abundant, its value drops. Information used to be scarce. Now it’s infinite. Analysis used to be […]
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Perplexity announces “Computer,” an AI agent that assigns work to other AI agents
Perplexity has introduced “Computer,” a new tool that allows users to assign tasks and see them carried out by a system that coordinates multiple agents running various models. The company claims that Computer, currently available to Perplexity Max subscribers, is “a system that creates and executes entire workflows” and “capable of running for hours or even months.” The idea is that the user describes a specific outcome—something like “plan and execute a local digital marketing campaign for my […]
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Component Centric Placement Using Deep Reinforcement Learning
Automated placement of components on printed circuit boards (PCBs) is a critical stage in placement layout design. While reinforcement learning (RL) has been successfully applied to system-on-chip IP block placement and chiplet arrangement in complex packages, PCB component placement presents unique challenges due to several factors: variation in component sizes, single- and double-sided boards, wirelength constraints, board constraints, and non-overlapping placement requirements. In this work, we adopt a component-centric layout for automating PCB component placement using RL: first, […]
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Few-Shot Continual Learning for 3D Brain MRI with Frozen Foundation Models
Foundation models pretrained on large-scale 3D medical imaging data face challenges when adapted to multiple downstream tasks under continual learning with limited labeled data. We address few-shot continual learning for 3D brain MRI by combining a frozen pretrained backbone with task-specific Low-Rank Adaptation (LoRA) modules. Tasks arrive sequentially — tumor segmentation (BraTS) and brain age estimation (IXI) — with no replay of previous task data. Each task receives a dedicated LoRA adapter; only the adapter and task-specific head […]
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Active Value Querying to Minimize Additive Error in Subadditive Set Function Learning
Subadditive set functions play a pivotal role in computational economics (especially in combinatorial auctions), combinatorial optimization or artificial intelligence applications such as interpretable machine learning. However, specifying a set function requires assigning values to an exponentially large number of subsets in general, a task that is often resource-intensive in practice, particularly when the values derive from external sources such as retraining of machine learning models. A~simple omission of certain values introduces ambiguity that becomes even more significant when […]
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