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Showing 7 open source projects for "which"
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Toloka-Kit
Toloka-Kit is a Python library for working with Toloka API
...There’s no need to validate JSON files and work with them directly. Support of both synchronous and asynchronous (via async/await) executions. Streaming support: build complex pipelines which send and receive data in real-time. For example, you can pass data between two related projects: one for data labeling, and another for its validation. AutoQuality feature which automatically finds the best fitting quality control rules for your project. -
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Diffgram
Training data (data labeling, annotation, workflow) for all data types
...This is aimed to reduce your data labeling bills and increase your Training Data Quality. Training Data is the art of supervising machines through data. This includes the activities of annotation, which produces structured data; ready to be consumed by a machine learning model. Annotation is required because raw media is considered to be unstructured and not usable without it. That’s why training data is required for many modern machine learning use cases including computer vision, natural language processing and speech recognition. -
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Cleanlab
The standard data-centric AI package for data quality and ML
cleanlab helps you clean data and labels by automatically detecting issues in a ML dataset. To facilitate machine learning with messy, real-world data, this data-centric AI package uses your existing models to estimate dataset problems that can be fixed to train even better models. cleanlab cleans your data's labels via state-of-the-art confident learning algorithms, published in this paper and blog. See some of the datasets cleaned with cleanlab at labelerrors.com. This package helps you... -
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DotVVM
Open source MVVM framework for Web Apps
...DotVVM comes with ready-made components you can use in your HTML files. The state and user interactions are handled in view models - C# classes. The controls render simple HTML which can be styled easily. MVVM pattern and data-binding expressions are used to access the UI components. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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5
Lightly
A python library for self-supervised learning on images
A python library for self-supervised learning on images. We, at Lightly, are passionate engineers who want to make deep learning more efficient. That's why - together with our community - we want to popularize the use of self-supervised methods to understand and curate raw image data. Our solution can be applied before any data annotation step and the learned representations can be used to visualize and analyze datasets. This allows selecting the best core set of samples for model training... -
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Acharya
A Data Centric annotation tool for your Named Entity Recognition
A data-centric annotation tool to increase the accuracy of your Named Entity Recognition projects which helps rapidly identify and fix labeling errors in your dataset. Import/export datasets in multiple formats, train a model and use it to aid in the annotation process. Setup an MLOps pipeline to experiment with different algorithms on the same data and increase their accuracy and performance in a data-centric way. Installation and Setup for Acharya are not required, Acharya runs the initial setup when run for the first time. ... -
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We developed a RNA-Seq Data Annotation Pipeline named RNADAP, which measure genes expression in isoform level, work with high speed and less memory usage. Besides, our pipeline can be compatible with results from different mapping software.
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