Shapelets VectorDB vs. Weaviate:
Head-to-Head Performance Comparison
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Main applications of vector databases
Vector databases store and process data as vectors, offering advantages in data analysis, machine learning, and information retrieval over relational, document, and graph databases. Key applications include semantic search, product recommendation, and anomaly detection. These databases excel in flexibility, scalability, and efficiency, making them highly suitable for handling diverse and large datasets.
Vector Databases with Bitmap Indexing
Explore the power of vector databases, accelerate performance with bitmap indexing. See how Shapelets REC revolutionizes data access speeds.
Million-Datapoint Series
Efficiency and precision in handling extensive data volumes
Smoothing Time Series
Create professional interfaces for your machine learning models effortlessly with Shapelets Platform. This tool allows you to design elegant, user-friendly web interfaces with minimal code, letting you focus on your model while Shapelets handles the rest.
PyConES Canarias 2023
We are announce our participation as Teide sponsors at PyCon España 2023, one of the most prestigious events in the Python community.
Shapelets: Develop Data Science Projects in 10 Minutes
Agile productivity solutions deliver substantial time savings