Data inundates us like never before—how can we hope to analyze it? Graphs (networks, not bar graphs) provide an elegant approach. Find out how to start with the Python NetworkX library to describe, visualize, and analyze "graph theory" datasets.
Harnessing the potential of machine learning for computer vision is not a new concept but recent advances and the availability of new tools and datasets have made it more accessible to developers.
In this article, Toptal Software Developer Teimur Gasanov demonstrates how you can create an app capable of identifying handwritten digits in under 30 minutes, including the API and UI.
Working with non-numerical data can be challenging, even for seasoned data scientists. To make good use of such data, it needs to be transformed. But how?
In this article, Toptal Data Scientist Yaroslav Kopotilov will introduce you to embeddings and demonstrate how they can be used to visualize complex data and make it usable.
IMDb ratings have genre bias: For example, dramas tend to score higher. Removing common feature bias and keeping unique characteristics, it's possible to create a new, refined score based on IMDb information.
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.