Showing 7 open source projects for "support vector machine"

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  • 1
    dlib

    dlib

    Toolkit for making machine learning and data analysis applications

    Dlib is a modern C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems. It is used in both industry and academia in a wide range of domains including robotics, embedded devices, mobile phones, and large high performance computing environments. Dlib's open source licensing allows you to use it in any application, free of charge. Good unit test coverage, the ratio of unit test lines of code to library lines of code is...
    Downloads: 10 This Week
    Last Update:
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  • 2
    electron-builder

    electron-builder

    A complete solution to package and build a Electron app

    A complete solution to package and build a ready-for-distribution Electron, Proton Native app for macOS, Windows and Linux with “auto update” support out of the box. You can use electron-builder only to pack your electron app in a AppImage, Snaps, Debian package, NSIS, macOS installer component package (pkg) and other distributable formats. Build and publish in parallel, using hard links on CI server to reduce IO and disk space usage. Docker images to build Electron app for Linux or Windows...
    Downloads: 21 This Week
    Last Update:
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  • 3
    SST

    SST

    Build serverless apps. Set breakpoints and test your functions locally

    SST is an open-source serverless application platform that deploys to your AWS account, helping you go from idea to IPO. Work on your local Lambda functions lives, without mocking or redeploying your app. Higher-level CDK constructs are made specifically for building serverless apps. Manage the resources in your application with the SST Console. Traditionally, we’ve built and deployed web applications where we have some degree of control over the HTTP requests that are made to our server....
    Downloads: 22 This Week
    Last Update:
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  • 4
    DALI

    DALI

    A GPU-accelerated library containing highly optimized building blocks

    The NVIDIA Data Loading Library (DALI) is a library for data loading and pre-processing to accelerate deep learning applications. It provides a collection of highly optimized building blocks for loading and processing image, video and audio data. It can be used as a portable drop-in replacement for built-in data loaders and data iterators in popular deep learning frameworks. Deep learning applications require complex, multi-stage data processing pipelines that include loading, decoding,...
    Downloads: 0 This Week
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  • 5
    Luigi

    Luigi

    Python module that helps you build complex pipelines of batch jobs

    ...You want to chain many tasks, automate them, and failures will happen. These tasks can be anything, but are typically long running things like Hadoop jobs, dumping data to/from databases, running machine learning algorithms, or anything else. You can build pretty much any task you want, but Luigi also comes with a toolbox of several common task templates that you use. It includes support for running Python mapreduce jobs in Hadoop, as well as Hive, and Pig, jobs. It also comes with file system abstractions for HDFS, and local files that ensures all file system operations are atomic.
    Downloads: 0 This Week
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  • 6
    Cyclops

    Cyclops

    An advanced platform for writing functional applications in Java 8

    Fast purely functional datastructures (Vector, Seq / List, LazySeq / LazyList, NonEmptyList, HashSet, TreeSet, TrieSet, HashMap, LinkedMap, MultiMap, TreeMap, BankersQueue, LazyString, Discrete Interval Encoded Tree, Zipper, Range, Tree, DifferenceList, HList, Dependent Map). Structural Pattern Matching API (deconstruct algebraic product and sum types). Improved type safety via the removal of unsafe APIs -- E.g.
    Downloads: 0 This Week
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  • 7
    pyTorch Tutorials

    pyTorch Tutorials

    Build your neural network easy and fast

    pyTorch Tutorials is an open-source collection of hands-on tutorials designed to teach developers how to build neural networks with the PyTorch framework. It covers the fundamentals of PyTorch from basic tensor operations to constructing full neural network models, making it suitable for beginners and intermediate learners alike. The project is structured around clear, executable Python scripts and Jupyter notebooks that demonstrate regression, classification, convolutional networks,...
    Downloads: 0 This Week
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