3 projects for "data processing" with 2 filters applied:

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  • 1
    RuVector

    RuVector

    Self-Learning, Vector Graph Neural Network, and Database built in Rust

    RuVector is part of the broader rUv ecosystem of AI engineering tools and focuses on enabling advanced vector-based processing and intelligent system development within agentic and AI-driven pipelines. The project fits into a larger vision of modular, composable AI infrastructure designed to support autonomous agents, data retrieval, and intelligent automation workflows. It emphasizes extensibility and interoperability with modern AI stacks, allowing developers to integrate vector operations into search, reasoning, or generative systems. ...
    Downloads: 8 This Week
    Last Update:
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  • 2
    Neural Network Visualization

    Neural Network Visualization

    Project for processing neural networks and rendering to gain insights

    nn_vis is a minimalist visualization tool for neural networks written in Python using OpenGL and Pygame. It provides an interactive, graphical representation of how data flows through neural network layers, offering a unique educational experience for those new to deep learning or looking to explain it visually. By animating input, weights, activations, and outputs, the tool demystifies neural network operations and helps users intuitively grasp complex concepts. Its lightweight codebase is...
    Downloads: 0 This Week
    Last Update:
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  • 3
    cnn-text-classification-tf

    cnn-text-classification-tf

    Convolutional Neural Network for Text Classification in Tensorflow

    The cnn-text-classification-tf repository by Denny Britz is a well-known educational implementation of convolutional neural networks for text classification using TensorFlow, aimed at helping developers and researchers understand how CNNs can be applied to natural language processing tasks. Based loosely on Kim’s influential paper on CNNs for sentence classification, this codebase demonstrates how to preprocess text data, convert words into learned embeddings, and apply multiple convolution filters to extract n-gram features that are then pooled and fed into a classifier. The project includes scripts for training, evaluation, and data handling, making it easy to run experiments on datasets such as movie reviews or other labeled text collections. ...
    Downloads: 0 This Week
    Last Update:
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