data science

Why construct things the hard way when you may design them the smart way? As a Supply Chain Data Scientist, I’ve explored various frameworks like LangChain and LangGraph to construct AI agents using Python. The illustration...

On March third, Google officially rolled out its Data Science Agent to most Colab users without spending a dime. This will not be something brand latest — it was first announced in December last...

previous article on organizing for AI (link), we checked out how the interplay between three key dimensions — ownership of outcomes, outsourcing of staff, and the geographical proximity of team members — can...

Ten years ago, everybody was fascinated by the cloud. It was the brand new thing, and firms that adopted it rapidly saw tremendous growth. Salesforce, for instance, positioned itself as a pioneer of this...

GenAI systems affect how we work. This general notion is well-known. Nonetheless, we're still unaware of the precise impact of GenAI. For instance, how much do these tools affect our work? Have they got...

As we've already seen with the essential components (Part 1, Part 2), the Hadoop ecosystem is continuously evolving and being optimized for brand new applications. Consequently, various tools and technologies have developed over time...

Introduction Let’s speak about Kubernetes probes and why they matter in your deployments. When managing production-facing containerized applications, even small optimizations can have enormous advantages. Aiming to cut back deployment times, making your applications higher react...

What's synthetic data? Data created by a pc intended to duplicate or augment existing data. Why is it useful? We've all experienced the success of ChatGPT, Llama, and more recently, DeepSeek. These language models are getting used...