4 projects for "deep learning ai" with 2 filters applied:

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  • 1
    turbovec

    turbovec

    A vector index built on TurboQuant, written in Rust with Python

    ...The project targets workloads where embedding search needs to be compact, efficient, and practical to integrate into Python applications. It avoids a separate training phase for the quantizer, which can simplify setup compared with systems that require codebook learning. TurboVec is useful for developers building retrieval, ranking, semantic search, recommendation, or AI memory systems. Its main value is combining Rust performance with a Python-facing workflow for modern vector search experiments and applications.
    Downloads: 0 This Week
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  • 2
    Cloud Storage FUSE

    Cloud Storage FUSE

    A user-space file system for interacting with Google Cloud Storage

    Cloud Storage FUSE is an open-source user-space file system adapter that allows Google Cloud Storage buckets to be mounted and accessed as if they were local file systems on a machine. This approach enables applications to interact with cloud storage using standard file system semantics, eliminating the need to rewrite code to use object storage APIs directly. The tool is particularly valuable in data-intensive workflows such as machine learning, where large datasets can be accessed on...
    Downloads: 2 This Week
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  • 3
    Grafana

    Grafana

    Leading open-source visualization and observability platform

    Grafana OSS is the leading open-source platform for visualization and observability. It enables teams to query, visualize, alert on, and explore telemetry data from multiple sources in a single interface. With support for 100+ data source plugins—including Prometheus, Loki, Elasticsearch, InfluxDB, SQL/NoSQL databases, and OpenTelemetry—Grafana helps teams correlate metrics, logs, and traces across applications and infrastructure. Users can build interactive dashboards with rich...
    Downloads: 18 This Week
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  • 4
    DeepCluster

    DeepCluster

    Deep Clustering for Unsupervised Learning of Visual Features

    DeepCluster is a classic self-supervised clustering-based representation learning algorithm that iteratively groups image features and uses the cluster assignments as pseudo-labels to train the network. In each round, features produced by the network are clustered (e.g. k-means), and the cluster IDs become supervision targets in the next epoch, encouraging the model to refine its representation to better separate semantic groups. This alternating “cluster & train” scheme helps the model...
    Downloads: 0 This Week
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