Panel: First Steps with Machine Learning

Panel: First Steps with Machine Learning

  • August 4, 2019
Table of Contents

Panel: First Steps with Machine Learning

This panel is a very diverse group, and I’m actually going to let them introduce themselves rather than me trying to butcher any names. This is all about answering my need, literally, my first steps. What should I be focused on as a software engineer wanting to get into ML and start using ML more convinced leadership on things that I want to do?

For example, I work for an edge company deploying use cases at edge, so I want to be able to use machine learning to be able to anomaly-detect things at the edge. I want to be able to reduce the amount of data that’s coming back to origins, things like that, so this is a self-serving panel for me.

Source: infoq.com

Tags :
Share :
comments powered by Disqus

Related Posts

Grafana Labs Teams Use Jaeger to Improve Query Performance Up to 10x

Grafana Labs Teams Use Jaeger to Improve Query Performance Up to 10x

Read More
Releasing Pythia for vision and language multimodal AI models

Releasing Pythia for vision and language multimodal AI models

Pythia is a deep learning framework that supports multitasking in the vision and language domain. Built on our open-source PyTorch framework, the modular, plug-and-play design enables researchers to quickly build, reproduce, and benchmark AI models. Pythia is designed for vision and language tasks, such as answering questions related to visual data and automatically generating image captions.

Read More
AQR’s Problem With Machine Learning: Cats Morph Into Dogs

AQR’s Problem With Machine Learning: Cats Morph Into Dogs

Machine learning has done magic, such as beating human chess champions. But in finance, expectations for the technology may need to come down a notch or two, according to quantitative firm AQR. Machine learning changes the way problems are solved.

Read More