There is no easy way to say this, but we have with heavy hearts decided to shut down PerceptiLabs - Learn more here:. Thank you all for being part of our journey and for all the support💛.

Use declarative deep learning with the Data Wizard in PerceptiLabs🚀. Learn more: #AI #DeepLearning #ComputerVision #TensorFlow

Visual modeling allows you to see how each operation transforms the data, and to rapidly iterate on your models⚡️. Easily tune hyperparameters and see live how it affects the model👀. #DeepLearning #TensorFlow #computervision

RT @NoCodeLuc: @PerceptiLabs. The fastest way to build, debug, and interpret neural networks.

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 @HuggingFace, @Kaggle, @TensorFlow, @PapersWithCode since they are all amazing sources 🙌

Need to quickly benchmark your model? . Use @PerceptiLabs' Overview screen to rapidly create multiple models for comparison from the same dataset. Then modify each model & use the Training & Evaluate views to make comparisons. Learn more:

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 #deeplearning 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.

Photos go in, reality comes out… and fast! 🌁. See you how @twominutepapers turns a few photos into video quickly & with no AI.

@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:

Have you checked out our #AI the Easy Way playlist?. The videos show you how to use #TransferLearning, how to deploy your model as an app, the befits of #lowcode #TensorFlow & more! Check it out:

Export your model as a pure @TensorFlow model or export our different bundles including scripts to easily deploy on your custom infrastructure 🚀. More options will be added to the public version soon 🙌 #ML #MachineLearning #TensorFlow

Join us for our next #LiveCoding event TOMORROW at 9AM PST!. In this live coding event our CTO + Co-Founder, @robert_lundberg , will build a Multi-Modal Regression model that can predict the price of houses using both meta data & images. Join here:

.@PerceptiLabs now supports different data storage structures. #ImageClassification supports subdirectories of images, #SegmentImages supports subdirectories for images & masks, & #MultiModel 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 & easily apply in @PerceptiLabs 🚀. We've integrated @HuggingFace, @Kaggle, @TensorFlow, @PapersWithCode since they are all amazing sources 🙌

You asked how to deploy, use, & test a model that has been exported by @PerceptiLabs. So, we added a @Gradio deployment target. This blog discusses the rationale behind it & how you can use it to test your model. #DeepLearning #MachineLearning #MLOps

Check out our new blog & discover why @PerceptiLabs added the @FastAPI deployment target. and get inspired about how you might build on that output. 💫 . #machinelearning #deeplearning #lowcode #TensorFlow .

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

.@PerceptiLabs is #MLOps made easy 🙌. #Lowcode is the future, check it out:. ✅ Versioning.🛠 Load and pre-process data.⚡ Modeling.📈 Train & interpret.📊 Evaluate & benchmark.🚀 Deploy

We have gathered public datasets for you to quickly try out different models on data similar to your use case, before you put in the effort of gathering your own data 🚀. The best thing is that anyone can contribute 🙌 Learn more here: