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A Visual Guide to Tuning Gradient Boosted Trees | Towards Data Science
Introduction My previous posts looked at the bog-standard decision tree and the wonder of a random forest. Now, to complete the triplet, I’ll visually explore gradient boosted trees! There are a bunch of gradient boosted tree libraries, including XGBoost, CatBoost, and LightGBM. However, for this I’m going to use sklearn’s one. Why? Simply because, compared […]
The Rise of Semantic Entity Resolution | Towards Data Science
Semantic entity resolution uses language models to bring an increased level of automation to schema alignment, blocking (grouping records into smaller, efficient blocks for all-pairs comparison at quadratic, n² complexity), matching and even merging duplicate nodes and edges. In the past, entity resolution systems relied on statistical tricks such as string distance, static rules or complex ETL to schema align, block, match and merge records. Semantic entity resolution uses representation learning to gain a deeper understanding of records’ meaning in the domain of a business to automate the same process as part of a knowledge graph factory.
A Focused Approach to Learning SQL | Towards Data Science
Data is everywhere, but how do you draw insights from it? Often, structured data is stored in relational databases, meaning collections of related tables of data. For instance, a company might store customer purchases in one table, customer demographics in another, and suppliers in a third table. These tables can then be joined together and […]
Docling: The Document Alchemist | Towards Data Science
Why do we still wrestle with documents in 2025? Spend some time in any data-driven organisation, and you’ll encounter a host of PDFs, Word files, PowerPoints, half-scanned images, handwritten notes, and the occasional surprise CSV lurking in a SharePoint folder. Business and data analysts waste hours converting, splitting, and cajoling those formats into something their Python […]
If we use AI to do our work – what is our job, then? | Towards Data Science
Images. Text. Audio. There’s no modality that is not handled by AI. And AI systems reach even further, planning advertisement and marketing campaigns, automating social media postings, … Most of this was unthinkable a mere ten years ago. But then, the first machine learning-driven algorithms did their initial steps: out of the research labs, into […]
Why Task-Based Evaluations Matter | Towards Data Science
This article is adapted from a lecture series I gave at Deeplearn 2025: From Prototype to Production: Evaluation Strategies for Agentic Applications. Task-based evaluations, which measure an AI system’s performance in use-case-specific, real-world settings, are underadopted and understudied. There is still an outsized focus in AI literature on foundation model benchmarks. Benchmarks are essential for advancing research and comparing broad, general capabilities, but they rarely translate cleanly into task-specific performance.
The Hungarian Algorithm and Its Applications in Computer Vision | Towards Data Science
Introduction Multi-object tracking (MOT) is a task in which an algorithm must detect and track multiple objects in a video. Most known algorithms are based on using simple detectors (e.g. YOLO) designed for processing individual images. The overall method involves separately using a detector on consecutive video frames and then matching the corresponding bounding boxes […]
Exploring Merit Order and Marginal Abatement Cost Curve in Python | Towards Data Science
To achieve the global temperature limit goals of 1.5°C by the end of the century set by the Paris Agreement, different institutions have come up with different scenarios. There is a consensus among the mitigation scenarios that the share of low-carbon technologies such as renewable energy needs to increase, and fossil fuels need to decline steadily in […]
LangGraph 201: Adding Human Oversight to Your Deep Research Agent | Towards Data Science
Losing control of your AI agent in the middle of the workflow is a common pain point. If you have built your own agentic applications, you’ve most likely already seen this happen. While LLMs nowadays are incredibly capable, they’re still not quite there yet to run fully autonomously in a complex workflow. For any practical […]