•  

Learning Tensorflow.js with Gant Laborde

0
0


Machine learning models must first be trained.  That training results in a model which must be serialized or packaged up in some way as a deployment artifact.  A popular deployment path is using Tensorflow.js to take advantage of the portability of JavaScript, allowing your model to be run on a web server or client.


Gant Laborde is Chief Innovation Officer at Infinite Red, a React Native consulting team and the author of Learning TensorFlow.js: Powerful Machine Learning in JavaScript from O’Reilly.  In this interview, we explore use cases for Tensorflow.js.


Sponsorship inquiries: sponsor@softwareengineeringdaily.com


The post Learning Tensorflow.js with Gant Laborde appeared first on Software Engineering Daily.


No comments yet...
Log in to comment
New
0 0 0
Today

FastMCP with Adam Azzam and Jeremiah Lowin

The Model Context Protocol, or MCP, gives developers a common way to expose tools, data, and capabil…
0 0 0
2026-04-02

SED News: OpenCode, AI Code vs. Shipped Code, and the LiteLLM Breach

SED News is a monthly podcast from Software Engineering Daily where hosts Gregor Vand and Sean Falco…
0 0 0
2026-03-31

FreeBSD with John Baldwin

FreeBSD is one of the longest-running and most influential open-source operating systems in the worl…
0 0 0
2026-03-26

Cilium, eBPF, and Modern Kubernetes Networking with Bill Mulligan

Modern cloud-native systems are built on highly dynamic, distributed infrastructure where containers…
0 0 0
2026-03-24

Games That Push Back with Bennett Foddy

Bennett Foddy is a legendary game designer known for creating wholly distinctive games such as QWOP,…
0 0 0
2026-03-19

Prettier and Opinionated Code Formatting with James Long

Developer tooling shapes how software gets written day to day, but the best tools often disappear in…

Software Engineering Daily

Technical interviews about software topics.

Log in to Follow

More episodes from Software Engineering Daily

Top Podcasts Top rated Podcasts

Recent visits Your last viewed items