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- Labeling AI
- Alternatives
The best alternatives to Labeling AI are Lobe, Apple, and Jovian. If these 3 options don't work for you, we've listed over 10 alternatives below.
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PromotedBest alternatives to Labeling AI
- Lobe is an easy-to-use visual tool that lets you build custom deep learning models, quickly train them, and ship them directly in your app without writing any code.
- We offer practical and industry-focused programs that help you learn technical skills, build real-world projects, and advance your career.
- A demo inspired by the Tensorflow playground, but a bit broader in depth and with more customization. Believe it or not, there was a period of time where not everything in Machine Learning was Deep Learning - and this site covers a good amount of traditional methods that are still quite relevant today. Feedback is welcome!
- Uber Engineering is all about providing an operating system for every day life, including safer, more reliable transportation solutions to move everything from people to food to other things. This community exists to discuss the technologies powering Uber and its products.
- Kobra is a visual programming language (like Scratch) for machine learning. ⚡️ Build ML models and apps super fast 🧱 Visual interface = no need to learn complicated syntax 📊 Built in dataset manager and editor 💬 Share your projects with the world
- Gauss enables any person with a smartphone and an internet connection to be a data labeler, our mobile app has unlocked a new labeler ecosystem. Our Enterprise Portal allows for Collaborative Data Labeling for Internal Projects across multiple data formats.
- As students in high school, we realised that even though it is amazing, machine learning is really difficult to implement into projects. To remove the hassle we faced ourselves, we created MLBlocks. -Train models with only 50 images per class -Create them without expensive GPUs -Deploy on any platform through our API -NO CODE REQUIRED
- All-in-one platform for massive-scale automated and collaborative data labeling. Ango Hub combines the best of automation & collaboration into a plugin based architecture. Annotate and manage all of your unstructured data with AI assistance and custom plugins.
- Anote is an AI assisted data labeling tool that leverages state of the art few shot learning to label unstructured text data, identify and fix mislabels, and access entirely new data sources. Where you label a few data points, and we label the rest.
- A no-code machine learning platform built to unleash the power of computer vision and automation. It's a smart, scalable, cost-effective ML API as a service platform that trains and integrates state-of-the-art machine learning and deep learning.
- With onetask, you can label AI training data on large-scale yourself. We combine Weak Supervision and Active Learning, so that you can easily find patterns in your data and only label records by hand that need human cognition.
- Malt empowers hackers to create labeled object detection datasets fast! You can quickly navigate through a video to find objects to label, and most impressively you can use a pre-trained TflowLite model to automatically place a bounding box around images!
- Intelec AI automates building and deploying machine learning models. Our mission is to make Artificial Intelligence available to everyone who needs it.
- Since launching in 2006, Amazon Web Services has been providing world-leading cloud technologies that help any organization and any individual build solutions to transform industries, communities, and lives for the better. As part of Amazon, we strive to be Earth’s most customer-centric company. We work backwards from our customers’ problems to provide them with cloud infrastructure that meets their needs, so they can reinvent continuously and push through barriers of what people thought was possible. Whether they are entrepreneurs launching new businesses, established companies reinventing themselves, non-profits working to advance their missions, or governments and cities seeking to serve their citizens more effectively—our customers trust AWS with their livelihoods, their goals, their ideas, and their data.
