As data professionals, we’re comfortable with tabular data…
Tabular data. Image by Author.
We can also handle words, json, xml feeds, and pictures of cats. But what about a cardboard box full of things like this?
(Image by Annie Spratt, Unsplash)
The info on this receipt wants so badly to be in a tabular database somewhere.…
In a world that focuses more on data, business leaders must understand vector thinking. At first, vectors may appear as complicated as algebra was in school, but they serve as a fundamental building block. Vectors are as essential as algebra for tasks like sharing a bill or computing interest. They underpin our digital systems for…
According to various sources, the average salary for Coding jobs is ~£47.5k in the UK, which is ~35% higher than the median salary of about £35k.
So, coding is a very valuable skill that will earn you more money, not to mention it’s really fun.
I have been coding professionally now for 4 years, working…
Introduction
The Attention Mechanism is often associated with the transformer architecture, but it was already used in RNNs. In Machine Translation or MT (e.g., English-Italian) tasks, when you want to predict the next Italian word, you need your model to focus, or pay attention, on the most important English words that are useful to make…
Why build things the hard way when you can design them the smart way?
As a Supply Chain Data Scientist, I’ve explored various frameworks like LangChain and LangGraph to build AI agents using Python.
Leveraging LLMs with LangChain for Supply Chain Analytics — A Control Tower Powered by GPT — (Image by Samir Saci)
The illustration above is from an article…
previous article on organizing for AI (link), we looked at how the interplay between three key dimensions — ownership of outcomes, outsourcing of staff, and the geographical proximity of team members — can yield a variety of organizational archetypes for implementing strategic AI initiatives, each implying a different twist to the product operating model.
Now…
As we have already seen with the basic components (Part 1, Part 2), the Hadoop ecosystem is constantly evolving and being optimized for new applications. As a result, various tools and technologies have developed over time that make Hadoop more powerful and even more widely applicable. As a result, it goes beyond the pure HDFS…
Nowadays, a large amount of data is collected on the internet, which is why companies are faced with the challenge of being able to store, process, and analyze these volumes efficiently. Hadoop is an open-source framework from the Apache Software Foundation and has become one of the leading Big Data management technologies in recent years.…
Despite the AI hype, many tech companies still rely heavily on machine learning to power critical applications, from personalized recommendations to fraud detection.
I’ve seen firsthand how undetected drifts can result in significant costs — missed fraud detection, lost revenue, and suboptimal business outcomes, just to name a few. So, it’s crucial to have robust…
1. Introduction
Ever since the introduction of the self-attention mechanism, Transformers have been the top choice when it comes to Natural Language Processing (NLP) tasks. Self-attention-based models are highly parallelizable and require substantially fewer parameters, making them much more computationally efficient, less prone to overfitting, and easier to fine-tune for domain-specific tasks [1]. Furthermore, the…