By and large, if you need a database, you can reach for one of the big names. But sometimes the one-size-fits-all approach doesn’t fit all.
Stories by Serdar Yegulalp
In newest challenge, Kaggle asks AI researchers to apply machine learning tools and techniques to answering questions about Covid-19.
Learn how to get Python up and running on Windows, MacOS, or Linux—and avoid the biggest pitfalls along the way.
Google's machine learning toolkit for Kubernetes helps data scientists manage machine learning workflows and deploy and scale models in production.
Microsoft has released DeepSpeed, designed to reduce memory use and train models with better parallelism on existing hardware.
Metaflow manages Python data science projects end-to-end, works with any machine learning library, and integrates with AWS cloud services.
Two Python libraries containing malicious code have been removed from the Python Package Index. Python’s official repository for third-party packages.
Learn how Docker and Kubernetes are changing application development and how these key container technologies fit together.
Microsoft has unveiled several new additions to its Azure ML offering for machine learning, including better integration with Python.
Much like customers, partners also require guidance on the key technologies and markets to pursue. Read the Channel Roadmap to build a blueprint for future success.