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| About
            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.
             | About
            Flower is an open source federated learning framework designed to simplify the development and deployment of machine learning models across decentralized data sources. It enables training on data located on devices or servers without transferring the data itself, thereby enhancing privacy and reducing bandwidth usage. Flower supports a wide range of machine learning frameworks, including PyTorch, TensorFlow, Hugging Face Transformers, scikit-learn, and XGBoost, and is compatible with various platforms and cloud services like AWS, GCP, and Azure. It offers flexibility through customizable strategies and supports both horizontal and vertical federated learning scenarios. Flower's architecture allows for scalable experiments, with the capability to handle workloads involving tens of millions of clients. It also provides built-in support for privacy-preserving techniques like differential privacy and secure aggregation.
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| Audience
        Enterprises requiring a solution that provides advanced parallelism for analytics, enabling performance at scale
         | Audience
        Machine learning practitioners and researchers in search of a tool to implement privacy-preserving, decentralized model training across diverse devices and platforms
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| Company InformationDask Founded: 2019 dask.org | Company InformationFlower Founded: 2023 Germany flower.ai/ | |||||
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         | Integrations
            
                
    Google Cloud Platform
            
            
         
            
                
    Anaconda
            
            
         
            
                
    Android
            
            
         
            
                
    Apple iOS
            
            
         
            
                
    Flyte
            
            
         
            
                
    Hugging Face
            
            
         
            
                
    Kedro
            
            
         
            
                
    Keras
            
            
         
            
                
    MXNet
            
            
         
            
                
    Microsoft Azure
            
            
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