Search Results for "ml"

TensorFlow.js is a library for machine learning in JavaScript. Develop ML models in JavaScript, and use ML directly in the browser or in Node.js. Use off-the-shelf JavaScript models or convert Python TensorFlow models to run in the browser or under Node.js. Retrain pre-existing ML models using your own data. Build and train models directly in JavaScript using flexible and intuitive APIs. Tensors are the core datastructure of TensorFlow.js They are a generalization of vectors and matrices...

The Learning Interpretability Tool (LIT, formerly known as the Language Interpretability Tool) is a visual, interactive ML model-understanding tool that supports text, image, and tabular data. It can be run as a standalone server, or inside of notebook environments such as Colab, Jupyter, and Google Cloud Vertex AI notebooks.

Data annotator for machine learning allows you to centrally create, manage and administer annotation projects for machine learning. Data Annotator for Machine Learning (DAML) is an application that helps machine learning teams facilitate the creation and management of annotations. Active learning with uncertain sampling to query unlabeled data. Project tracking with real-time data aggregation and review process. User management panel with role-based access control.

An open-source file sharing app built using Next.js and Perplexity. The app employs ML-KEM-1024, ChaCha20, Serpent-256, and HMAC-SHA512 to ensure data confidentiality and integrity. The app is also equipped with a dedicated password vault. Check it out at https://plum-harbor.netlify.app/ GitHub page: https://github.com/Northstrix/plum-harbor Codeberg page: https://codeberg.org/Northstrix/plum-harbor The app is available in English and Hebrew. German version is available here...

... run the unit tests for any of the models by running "yarn test" inside a directory. Use off-the-shelf JavaScript models or convert Python TensorFlow models to run in the browser or under Node.js. Build and train models directly in JavaScript using flexible and intuitive APIs. Develop ML models in JavaScript, and use ML directly in the browser or in Node.js.