On the verge of new AI possibilities

Go Time: Golang, Software Engineering

In this episode Jaana and Mat are joined by Daniel and Miriah to dive into AI in Go. Why has python historically had a bigger foothold in the AI scene? Is machine learning in Go growing? What libraries and tools are out there for someone looking to get started with AI? And where do you start if you don’t have enough data for your own models?

Join the discussion

Changelog++ members support our work, get closer to the metal, and make the ads disappear. Join today!

Sponsors:

• DigitalOcean – DigitalOcean’s developer cloud makes it simple to launch in the cloud and scale up as you grow. They have an intuitive control panel, predictable pricing, team accounts, worldwide availability with a 99.99% uptime SLA, and 24/7/365 world-class support to back that up. Get your $100 credit at do.co/changelog.
• Algorithms with Go – A free Go course where panelist Jon Calhoun teaches you how algorithms and data structures work, how to implement them in Go code, and where to practice at. Great for learning Go, learning about algorithms for the first time, or refreshing your algorithmic knowledge.
• Fastly – Our bandwidth partner. Fastly powers fast, secure, and scalable digital experiences. Move beyond your content delivery network to their powerful edge cloud platform. Learn more at fastly.com.
• Rollbar – We move fast and fix things because of Rollbar. Resolve errors in minutes. Deploy with confidence. Learn more at rollbar.com/changelog.

Featuring:

• Daniel Whitenack – Website, GitHub, X
• Miriah Peterson – Website, GitHub, LinkedIn, X
• Mat Ryer – Website, GitHub, LinkedIn, X
• Jaana Dogan – Website, GitHub, X

Show Notes:

• The Practical AI podcast - Our sister podcast with Daniel Whitenack and Chris Benson
• Gopher’s Slack #data-science - This channel is a great place to ask questions and get started with AI in Go.
• Go Num Libraries - Large family of libraries for statistics, etc. Great for AI.
• Gorgonia - Library that helps facilitate machine learning in Go.
• Awesome Machine Learning - The Go section of this repo is helpful for finding other AI and ML libraries in Go.
• Gopher Data - A hub for users and developers of Go data process, analytics, etc.
• spaCy and thinc - Python Deep Learning tools that introduced type checking, suggesting this is a valuable thing in ML.
• Google Cloud AutoML - Google’s machine learning models, which can be a good starting point for many orgs.
• Azure Machine Learning - Microsoft’s machine learning tooling and offering. Also a great place for many orgs to start.
• Packyderm - Data science platform with an open source offering.
• Go West Conference - A Go conference in Utah that our guest Miriah helps organize.

Something missing or broken? PRs welcome!