machine learning

I computing 7 years ago, just after my master’s degree. At the moment, the sphere was filled with excitement but additionally skepticism. Today, quantum computing stands out as an emerging technology, alongside HPCs...

of a series about distributed AI across multiple GPUs: Introduction Within the previous post, we saw how Distributed Data Parallelism (DDP) hastens training by splitting batches across GPUs. DDP solves the throughput problem, however it...

Although continuous variables in real-world datasets provide detailed information, they should not at all times probably the most effective form for modelling and interpretation. That is where variable discretization comes into play. Understanding variable discretization...

. You’re three weeks right into a churn prediction model, hunched over a laptop, watching a Bayesian optimization sweep crawl through its 2 hundredth trial. The validation AUC ticks from 0.847 to 0.849. You...

working as a machine learning engineer at a Big Tech company. On paper, I had a dream job: Flexible working Smart and friendly colleagues Great perks and advantages Good work-life balance Barely any meetings And my compensation was well over...

Introduction a continuous variable for 4 different products. The machine learning pipeline was in-built Databricks and there are two major components.  Feature preparation in SQL with serverless compute. Inference on an ensemble of several hundred models using...

five minutes on LinkedIn or X, you’ll notice a loud debate in the info science industry. It’s been out for some time now, but this week, it finally caught my attention. As much as...

Introduction that always operates with surprising inefficiency: manual processes, piles of paperwork, legal complexities. Many corporations still run on paper or Excel and don’t even collect data on their shipments. But what if an organization...