Ango Hub alternatives

The fastest and most powerful end-to-end platform for Machine Learning and Deep Learning. Accelerate Machine Learning projects.

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!

Git-based data science. Apply version control machine learning development, make your repo the backbone of your project, and standardize best practices across your team.

Lionbridge’s 500,000+ annotators label your text, audio, image, and video data for machine learning. Using our custom-built platform, we can: 🤖 Create chatbot training data 🖼 Label images and video 😍 Build sentiment analysis datasets 👩‍💻 Source annotators from around the world 💬 Improve machine translation

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.

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.

Datasaur builds data labeling tools for natural language processing. Using intelligent models and improved workforce management, Datasaur helps ML leaders better manage their team and improve the quality of their training data.

Labeling AI is a deep learning-based technology that automatically labels (annotates) large amounts of data based on a small amount of pre-labeled data available, with minimal human intervention required only to review the final result.