Compare the Top Data Science Software in the UK as of November 2025 - Page 5

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    Dask

    Dask

    Dask

    Dask is open source and freely available. It is developed in coordination with other community projects like NumPy, pandas, and scikit-learn. Dask uses existing Python APIs and data structures to make it easy to switch between NumPy, pandas, scikit-learn to their Dask-powered equivalents. Dask's schedulers scale to thousand-node clusters and its algorithms have been tested on some of the largest supercomputers in the world. But you don't need a massive cluster to get started. Dask ships with schedulers designed for use on personal machines. Many people use Dask today to scale computations on their laptop, using multiple cores for computation and their disk for excess storage. Dask exposes lower-level APIs letting you build custom systems for in-house applications. This helps open source leaders parallelize their own packages and helps business leaders scale custom business logic.
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    Cloudera Data Science Workbench
    Accelerate machine learning from research to production with a consistent experience built for your traditional platform. With Python, R, and Scala directly in the web browser, Cloudera Data Science Workbench (CDSW) delivers a self-service experience data scientists will love. Download and experiment with the latest libraries and frameworks in customizable project environments that work just like your laptop. Cloudera Data Science Workbench provides connectivity not only to CDH and HDP but also to the systems your data science teams rely on for analysis. Cloudera Data Science Workbench lets data scientists manage their own analytics pipelines, including built-in scheduling, monitoring, and email alerting. Quickly develop and prototype new machine learning projects and easily deploy them to production.
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    IBM SPSS Modeler
    IBM SPSS Modeler is a leading visual data science and machine learning (ML) solution designed to help enterprises accelerate time to value by speeding up operational tasks for data scientists. Organizations worldwide use it for data preparation and discovery, predictive analytics, model management and deployment, and ML to monetize data assets. IBM SPSS Modeler automatically transforms data into the best format for the most accurate predictive modeling. It now only takes a few clicks for you to analyze data, identify fixes, screen out fields and derive new attributes. Leverage IBM SPSS Modeler’s powerful graphics engine to bring your insights to life. The smart chart recommender finds the perfect chart for your data from among dozens of options, so you can share your insights quickly and easily using compelling visualizations.
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    Daft

    Daft

    Daft

    Daft is a framework for ETL, analytics and ML/AI at scale. Its familiar Python dataframe API is built to outperform Spark in performance and ease of use. Daft plugs directly into your ML/AI stack through efficient zero-copy integrations with essential Python libraries such as Pytorch and Ray. It also allows requesting GPUs as a resource for running models. Daft runs locally with a lightweight multithreaded backend. When your local machine is no longer sufficient, it scales seamlessly to run out-of-core on a distributed cluster. Daft can handle User-Defined Functions (UDFs) in columns, allowing you to apply complex expressions and operations to Python objects with the full flexibility required for ML/AI. Daft runs locally with a lightweight multithreaded backend. When your local machine is no longer sufficient, it scales seamlessly to run out-of-core on a distributed cluster.
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    ZinkML

    ZinkML

    ZinkML Technologies

    ZinkML is a zero-code data science platform designed to address the challenges faced by organizations in leveraging data effectively. By providing a visual and intuitive interface, it eliminates the need for extensive coding expertise, making data science accessible to a broader range of users. ZinkML streamlines the entire data science lifecycle, from data ingestion and preparation to model building, deployment, and monitoring. Users can drag-and-drop components to create complex data pipelines, explore data visually, and build predictive models without writing a single line of code. The platform also offers automated feature engineering, model selection, and hyperparameter tuning, accelerating the model development process. Moreover, ZinkML provides robust collaboration features, enabling teams to work together seamlessly on data science projects. By democratizing data science, we empower companies to extract maximum value from their data and drive better decision-making.
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    Appier AIXON
    AIXON is a data science platform that unifies and enriches existing customer data to help you better understand your audience, and run AI models to easily predict their future action. Enrich profiles with internal and external insights to form a holistic view of users. Use AI brains to find the best pattern for your marketing strategies within seconds. Take action directly and easily with insights generated from AI brains to all channels. AIXON creates a 360-degree view of your audience by unifying data from different sources like apps, websites and CRM. Enrich your audience profiles by combining this data with users’ external digital footprint from Appier’s unique cross-screen database. Take advantage of existing AI models or build your own to generate powerful predictions within minutes. The platform enables you to create segments based on user interests or personas, find lookalikes, compare audiences and predict future action such as conversions.
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    SAS Enterprise Miner
    Streamline the data mining process to develop models quickly. Understand key relationships. And find the patterns that matter most. Dramatically shorten model development time for your data miners and statisticians. An interactive, self-documenting process flow diagram environment efficiently maps the entire data mining process to produce the best results. And it has more predictive modeling techniques than any other commercial data mining package. Why not use the best? Business users and subject-matter experts with limited statistical skills can generate their own models using SAS Rapid Predictive Modeler. An easy-to-use GUI steps them through a workflow of data mining tasks. Analytics results are displayed in easy-to-understand charts that provide the insights needed for better decision-making. Create better-performing models using innovative algorithms and industry-specific methods. Verify results with visual assessment and validation metrics.