Articles tagged with
machine learning

19 May 2025

Unlock faster data processing for Machine Learning: reducing pivoting time from hours to minutes

Training Machine Learning models on big data isn’t just about fitting the model itself — it’s about efficiency at every stage of the process. While much attention is given to optimizing model training itself, the earlier phases can be just as, if not more, critical to the overall performance. In this article, we take a deep dive into what happens before we actually invoke model.fit(), focusing on the data pivoting stage. We are taking you on a journey through various pivoting solutions, exploring both pitfalls and interesting optimizations. The goal is simple: make this process highly efficient — in terms of processing time and memory usage. So, buckle up!


07 Mar 2025

How to create a synthetic annotator? The process of developing a domain-specific LLM-as-a-Judge.

In this blogpost we want to introduce the topic of using a Large Language Model (LLM) as an evaluator — a novel approach to tackling the complexities of evaluating advanced machine learning systems, particularly in tasks like Automatic Summarization, Text Generation, and Machine Translation, where traditional metrics struggle to capture nuances like cross-lingual accuracy and bias detection.


18 Apr 2023

Trust no one, not even your training data! Machine learning from noisy data

Label noise is ever-present in machine learning practice. Allegro datasets are no exception. We compared 7 methods for training classifiers robust to label noise. All of them improved the model’s performance on noisy datasets. Some of the methods decreased the model’s performance in the absence of label noise.



19 Dec 2016

Deep learning for frame detection in product images

At Allegro we are faced with a technical challenge: how to recognize whether a given image (a product thumbnail) shows just a product itself. One of the things that we would like to detect is when the product is surrounded by a frame. In this post we would like to present our approach for detecting a frame in the image.