2min chapter

DevOps Paradox cover image

DOP 222: Finding Performance Bottlenecks With Ddosify

DevOps Paradox

CHAPTER

How to Validate Your Model

We have the data and for example, OpenAI with Azure supports with pre-training. So we've trained it. So how do I know that my model is valid? We will split the data sets into training set and validation set. The training set consists of training and we will check the model with our validation set if accuracy is good. And what do you determine to be goes well? It passes 80%, 90%. so again, early on, I would imagine the number would be lower,. but over time, as you feed it more training data, the validation data is also going to be growing.

00:00

Get the Snipd
podcast app

Unlock the knowledge in podcasts with the podcast player of the future.
App store bannerPlay store banner

AI-powered
podcast player

Listen to all your favourite podcasts with AI-powered features

Discover
highlights

Listen to the best highlights from the podcasts you love and dive into the full episode

Save any
moment

Hear something you like? Tap your headphones to save it with AI-generated key takeaways

Share
& Export

Send highlights to Twitter, WhatsApp or export them to Notion, Readwise & more

AI-powered
podcast player

Listen to all your favourite podcasts with AI-powered features

Discover
highlights

Listen to the best highlights from the podcasts you love and dive into the full episode