machine learning

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...

Do you see yourself as a full-stack developer? How does your experience across the entire stack (from frontend to database) change the way you view the information scientist role? I do, but not within the...

project involving the construct of propensity models to predict customers’ prospective purchases, I encountered feature engineering issues that I had seen quite a few times before. These challenges might be broadly classified into two categories: 1)...

is incredibly effective at quickly build up recent applications. That is, in fact, super useful for any programming task, whether it's working on an existing legacy application or a brand new codebase. Nevertheless, from...

is an element of a series about distributed AI across multiple GPUs: Introduction Distributed Data Parallelism (DDP) is the primary parallelization method we’ll have a look at. It’s the baseline approach that’s all the time utilized in...