PerceptiLabs

Together with our community, we are gathering public datasets and State-of-the-Art models for everyone to use & easily apply in PerceptiLabs 🚀

We've integrated Hugging Face, Kaggle, , and Papers With Code since they are all amazing sources 🙌

With data-centric deep learning, projects are centered around the data to easily keep track of model and dataset versions ✅

This is enabled by default in PerceptiLabs, check it out 👇

Think your model is awesome? Think again.🤔

In this blog, we'll review some metrics to evaluate your model to uncover whether it's actually solving your problem.

Using Evaluations and Comparisons to Make Awesome DL Models Think your DL model is awesome? Think again. In this blog, we'll review some metrics to evaluate your model to uncover whether it's actually solving your problem.

PerceptiLabs calculates Precision (aka positive predictive value), Recall (aka sensitivity), and F1 Score for you (aka F-score or F-measure).

You can see all three updated in real-time during training, & the first two in our Evaluate View.👌🏼

Read more: docs.perceptilabs.com/perceptilabs/advanced/ui-overview/test-view

Evaluate View

Have you checked out our AI the Easy Way playlist?

The videos show you how to use , how to deploy your model as an app, the befits of low-code and more! Check it out: https://www.youtube.com/playlist?list=PLhDSeRDt1gii6RYfIOVKLkHeoTidNVfCm

Join us for our next event TOMORROW at 9AM PST!

In this live coding, our CTO + Co-Founder will build a Multi-Modal (multiple input types) Regression model that is able to predict the price of houses using both meta data and images.

Use this link to join:

PerceptiLabs Live Coding: Predicting house prices using Multi-Modal Regression Robert Lundberg, CTO and Co-founder of PerceptiLabs, will build a Multi-Modal (multiple input types) Regression model that is able to predict the price of ho...

PerceptiLabs now supports different data storage structures.

supports subdirectories of images, supports subdirectories for images and masks, and supports images in relative paths defined in your CSV file.💫

Together with our community, we are gathering public datasets and State-of-the-Art models for everyone to use and easily apply in PerceptiLabs 🚀

We've integrated Hugging Face, Kaggle, TensorFlow, since they are all amazing sources 🙌

Our dev community asked how to deploy, use, and even test a model that has been exported by PerceptiLabs.

So, we added a deployment target. This blog discusses the rationale behind this target and how you can use it to test your model >>> blog.perceptilabs.com/integrations-gradio-for-quick-and-easy-model-testing

Integrations: Gradio for Quick and Easy Model Testing You asked how to deploy, use, and even test a model that has been exported by PerceptiLabs. So, we added a Gradio deployment target. This blog discusses the rationale behind this target and how you can use it to test your model.

Check out our new blog and discover why PerceptiLabs added the deployment target... and get inspired about how you might build on that output. 💫

Integrations: FastAPI for Fast SaaS Application Deployments This blog shows why PerceptiLabs added the FastAPI deployment target, and to inspire how you might build on that output.

With auto-generated metrics, you can quickly understand your model 👀 Track the gradient to easily see if your model is learning 📊

Try it out: perceptilabs.com