Showing 4 open source projects for "deep"

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  • 1
    Aisthully Desktop  Suite

    Aisthully Desktop Suite

    The Freedom to Create. The Power to Master.

    Aisthully™ Suite The Freedom to Create. The Power to Master. A complete, downloadable learning ecosystem for Windows. Aisthully combines a professional-grade quiz creation tool (Quiz Studio) with a powerful, analytics-driven study application (Quiz Player). Stop using rigid, one-size-fits-all tools. Start building and mastering your curriculum. The "Quiz Studio" An expert workshop for anyone who teaches. This is where you build your lessons, quizzes, and exams with unparalleled...
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  • 2
    jieba

    jieba

    Stuttering Chinese word segmentation

    ...The search engine mode, on the basis of the precise mode, divides the long words again to improve the recall rate, which is suitable for word segmentation in search engines. The paddle mode uses the PaddlePaddle deep learning framework to train the sequence labeling (bidirectional GRU) network model to achieve word segmentation. Also supports part-of-speech tagging. To use paddle mode, you need to install paddlepaddle-tiny, pip install paddlepaddle-tiny==1.6.1. Currently paddle mode supports jieba v0.40 and above. For versions below jieba v0.40, please upgrade jieba, pip install jieba --upgrade.
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  • 3
    A Programmer's Guide to English

    A Programmer's Guide to English

    English study guide v1.2 written specifically for programmers

    ...The sooner you understand that language learning has no skills, the less time and money will be wasted on various materials and experiences, and the fewer detours you will make. This guide will dig deep into the essence of language learning (mainly in Chinese for example) and think in a way that programmers can understand easily, and provide their own deductions based on the essence. Training methods and experience are for reference. The most important thing is that you have to design your own training methods based on the essence.
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  • 4
    Donatus is an on-going project consisting of Python, NLTK-based tools and grammars for deep parsing and syntactical annotation of Brazilian Portuguese corpora. It includes a user-friendly graphical user interface for building syntactic parsers with the NLTK, providing some additional functionalities.
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