Data

It’s crucial to balance accuracy and efficiency when labeling datasets for machine learning—especially when LLMs are involved. In this article we explore a variety of techniques and assess the optimal labeling methods for different projects.

Security engineering is a fast-moving field, and getting left behind is not an option. This ask-me-anything-style Q&A covers compliance frameworks, security checks, and the importance of a DevSecOps approach.

Image labeling can be a tedious, time-consuming task, compounded by the sheer volume of data needed to train deep neural networks. This article breaks down large data set processing and explains how a new SaaS product can help automate image labeling.

Data warehouses aren’t exactly a new concept, but industry demand for data science services, coupled with the rise of AI and machine learning, is making them more relevant than ever.

In this post, Toptal Data Warehouse Developer Chamitha Wanaguru outlines three basic principles you need to keep in mind when developing a new data warehouse.

Although database programming does not evolve at nearly the same pace as traditional application programming, recent advancements in several fields are bringing new techniques and technologies within the reach of small and independent developers.

In this guide, Toptal Freelance Software Engineer Jeffrey Shumaker explains how developers can quickly and easily tap these methods to identify database issues they may not even be aware of, and how they can build excellent data mining tools without spending a lot on expensive software licenses.