Integration of Python for data science, graph processing for NoSQL-like functionality, and it runs on Linux as well as Windows. At almost 30 years of age, Microsoft's flagship database has learned ...

This repository contains the code for Team 1678's data-processing Server. For an in-depth explanation of our scouting system, please see our 2025 Whitepaper. Fork the server repository and clone it ...

Text data. First, it’s worth noting Python’s extensive built-in text-processing capabilities. However, many natural language processing techniques, such as tokenization and lemmatization, may be done ...

Data Flexibility: You can use diverse data sources, from open-source geospatial datasets to your own custom data, bringing unique perspectives to your maps. Learning Opportunity: Building your own ...

This new capability brings Python to the data and runs code inside secure SQL Server using the proven extensibility mechanism built in SQL Server 2016. Easy deployment: Once you have the Python model ...

The best parallel processing libraries for Python. Ray: Parallelizes and distributes AI and machine learning workloads across CPUs, machines, and GPUs.; Dask: Parallelizes Python data science ...

In this 4-hour workshop, students will learn basic data processing skills using Python. Attendees will learn how to import code from other modules and packages to take advantage of the existing Python ...

Natural language processing, or NLP for short, is best described as “AI for speech and text.” The magic behind voice commands, speech and text translation, sentiment analysis, text ...