Introducing Visual AI for DataRobot Automated Machine Learning
Visual AI is New in DataRobot 6.0
In Release 6.0 of DataRobot, we are thrilled to announce a ground-breaking new capability in our Automated Machine Learning product. DataRobot Visual AI gives you the ability to easily incorporate image data into your machine learning models alongside tabular and text-based data types. This enables your organization to get value from computer vision, right away – all with the same DataRobot usability, workflow, visuals, and other UI features you know and love.
Click image to see the full screenshot.
Analysts and data scientists of all skill levels can now drag and drop images into DataRobot to prepare, build, and deploy highly accurate deep learning models, in a fraction of the time compared to alternative tools. You can get started with just a few hundred images, so models can be trained in minutes or hours (not days), and the best part is, you don’t have to purchase expensive Graphical Processing Units (GPUs). DataRobot Visual AI is optimized to perform best on the hardware you already have in place.
With Visual AI, you can focus on solving business problems with image data without having to worry about gaining deep learning skills and spending money on infrastructure before you’ve built your first model.
How Do Organizations Use Visual AI?
Visual AI can be used across all industries in a wide variety of use cases. Retailers can use computer vision to improve the customer experience, detect when a product is out-of-stock on store shelves, or even watch for suspicious activity to help with loss prevention. Manufacturers can use Visual AI to identify product defects in real-time. As the parts and components come off their production line, images can be fed into their model to flag potential defects and avoid problems further downstream.
Insurance companies can conduct more consistent and accurate vehicle damage assessments to help reduce fraud and streamline the claims process. Healthcare providers can use image-based neural networks to automate the examination and diagnosis of health issues from MRI’s, CAT scans, and X-rays.
Above: Classifying blood diseases with Visual AI. Click image to see the full screenshot.
During the recent Visual AI private beta program, our customers had a varying number of problems they were able to tackle. From using images of gas stations to help better plan where to focus marketing spend, to the automated labeling of apparel from fashion photography for a leading eCommerce website.
Images. But Not Just Images
Visual AI allows you to build binary and multiclass classification and regression models with images. You can use it to build completely new image-based models, for example, to detect defects in steel or classify diseases in plants. You can also use it to add images as new features to existing models. This helps improve model accuracy from the fresh perspectives that images provide. For example, a hospital readmissions model built on tabular data, with features such as diagnosis, age, and gender can be enhanced with more diverse information such as surgeon notes, and with Visual AI, images from the patient’s MRI.
Above: DataRobot model Blueprints handle diverse types of data. Click image to see the full screenshot.
With Visual AI, we have shifted the market for image-based machine learning and computer vision. Now anyone using our Automated Machine Learning product can get value from their image data. Moreover, the ability to blend diverse types of data together in a single model is truly unique to DataRobot and is a game changer. We can’t wait to see how our customers take advantage of this to innovate in completely new ways.
Just How Easy is Visual AI to Use?
In a word – simple. This is what you do in 10 easy steps:
|1. Create your zip file.|
Put your images into different folders to classify them or use a csv file if you want to add lots of additional features. Then zip everything up (check out our Community article that describes this process in more detail).
Either drag your images straight into a new project or upload the zip file into DataRobot’s AI Catalog to share the image dataset with others.
|3. Pick your target and hit Start.|
Just like you do with a non-image project today. It’s literally that easy.
|4. Explore your image dataset.|
Our automated EDA will show you lots of interesting statistics about your dataset features, including the identification of missing and duplicate images.
|Click image to see the full screenshot|
|7. Tune and tweak (if that’s your thing).|
If you want to refine your model before you deploy it, we expose all of the models advanced hyperparameters for you to play with.
|Click image to see the full screenshot|
|8. Click to deploy.|
Congratulations! With a single click, you just deployed your image model into your production environment.
|Click image to see the full screenshot|
|10. Go buy a cape. You’re a deep-learning super hero, you should wear one.|
Wait…What? No GPUs?!
Yes, you heard that correctly. To get started with Visual AI you just use the DataRobot environment you already have in place today. You don’t need to go out and purchase a bunch of expensive GPUs. This is because DataRobot Visual AI ships with pre-trained neural networks that can be used to build your model in a fraction of the time, and with a much smaller volume of images, than training a neural network from scratch. What’s more, right out of the box, accuracy is more than comparable, if not better than many models trained from the ground up.
In a recent test we used Visual AI to build a multiclass model based on ~14K images of natural scenes around the world (e.g. buildings, forests, streets, mountains, etc) from a competition published by Intel on Analytics Vidhya. We were staggered with the results. Visual AI trained roughly 40 models in just over two hours using commodity hardware only (i.e. no GPUs). Our accuracy right out of the box was just over 92% and with a little tuning we added another couple of percentage points. Not only were these results impressive in terms of accuracy and performance, but the fact that this test was performed by a business analyst with minimal data science experience and absolutely no deep learning skills at all, is simply amazing.
Above: DataRobot’s Confusion Matrix shows high model accuracy across all classes. Click image to see the full screenshot
Get Your Hands on Visual AI Today
Visual AI is part of DataRobot 6.0. If you’re an existing DataRobot Automated Machine Learning customer, you need to contact our customer support team to request the feature be enabled for your account. It’s available in our Managed AI Cloud today, and if you are running DataRobot v6.0 on-premise or in a private cloud, your DataRobot account team will help you enable it.
Build models with Visual AI right now using DataRobot Automated Machine Learning on the infrastructure you already have in place. It’s easy to use, so you don’t need deep learning expertise, and it gives you accurate models that are easy to understand. So you can explain every single prediction to those that need to know. When you’re ready, you can deploy your models with a single click, and then monitor and manage them to keep them accurate. You can even update them without interrupting service.
At DataRobot we are proud to bring Visual AI to the market. It is truly unique in the field of automated computer vision and unlocks new use cases, never before possible as well as improving your existing models. So what are you waiting for? Take your AI strategy to the next level with Visual AI today.
More Information on Visual AI
You can also visit the DataRobot Community to learn more about DataRobot 6.0 and watch a demo of Visual AI.
The Next Generation of AI
DataRobot AI Platform is the next generation of AI. The unified platform is built for all data types, all users, and all environments to deliver critical business insights for every organization. DataRobot is trusted by global customers across industries and verticals, including a third of the Fortune 50.
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