Category: Machine Learning
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Top Vector Databases for AI and ML
Vector databases are essential for AI and machine learning, particularly for handling high-dimensional vectors from large language models. This article compares popular databases like LanceDB, Pinecone, and Milvus, highlighting their unique features and ideal use cases. Choosing the right database depends on scalability, performance, and integration for various applications.
Best Open-Source Annotation Tools for NLP and ML
When creating high-quality datasets for machine learning, annotation is crucial. Open-source annotation tools like Label Studio, Doccano, INCEpTION, brat, and TagTog offer versatile features for text, image, video, and audio data. Each tool has specific strengths and limitations, making them suitable for different annotation tasks and user needs.
Multi-Language NLP Annotation Made Easy with Doccano
Doccano is a popular open-source annotation tool for NLP tasks. With a web-based interface, it supports multilingual annotation, various annotation types, easy collaboration, and data import/export. It can be set up via Docker or directly installed and has use cases in healthcare, legal, sentiment analysis, and academic research. Its future…
How to Choose the Best LLM Evaluation Tool in 2024
The implementation and utilization of large language models (LLMs) in various industries emphasize the significance of evaluation for their effectiveness. Open-source frameworks like DeepEval, UpTrain, RAGAs, Deepchecks, and Arize AI Phoenix provide unique features for assessing LLMs, enabling precision, simplification, and specialized analysis for different applications. These tools help in…
Visual block for ML – Unleash your creativity
You can quickly prototype workflows by connecting drag-and-drop ML components, including models, user inputs, processors, and visualizations.