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    Build AI Apps with Gemini 3 on Vertex AI

    Access Google’s most capable multimodal models. Train, test, and deploy AI with 200+ foundation models on one platform.

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    Go from Data Warehouse to Data and AI platform with BigQuery

    Build, train, and run ML models with simple SQL. Automate data prep, analysis, and predictions with built-in AI assistance from Gemini.

    BigQuery is more than a data warehouse—it's an autonomous data-to-AI platform. Use familiar SQL to train ML models, run time-series forecasts, and generate AI-powered insights with native Gemini integration. Built-in agents handle data engineering and data science workflows automatically. Get $300 in free credit, query 1 TB, and store 10 GB free monthly.
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  • 1
    generativeart

    generativeart

    Create Generative Art with R

    generativeart is an R package for creating algorithmic art by computing the positions of many thousands of points according to user-defined mathematical formulas with randomized parameters. Each render uses a seed to introduce controlled randomness, so every image is unique while remaining reproducible when the same seed and formula are reused. The package logs the seed, formula, and file name to a CSV, which makes it easy to catalog outputs, re-generate favorites, and track experiments. A...
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  • 2
    Harmony Data Integration

    Harmony Data Integration

    Fast, sensitive and accurate integration of single-cell data

    Harmony is a general-purpose R package with an efficient algorithm for integrating multiple data sets. It is especially useful for large single-cell datasets such as single-cell RNA-seq. Harmony has been tested on R versions =4. Please consult the DESCRIPTION file for more details on required R packages. Harmony has been tested on Linux, OS X, and Windows platforms.
    Downloads: 0 This Week
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  • 3
    AnomalyDetection

    AnomalyDetection

    Anomaly Detection with R

    AnomalyDetection is an R package developed by Twitter for detecting anomalies in seasonal univariate time series. It implements the Seasonal Hybrid Extreme Studentized Deviate (S‑H‑ESD) test, which reliably identifies both global and local outliers in data with trends and seasonality—commonly applied to system metrics, engagement data, and business KPIs.
    Downloads: 0 This Week
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