Showing 83 open source projects for "format"

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  • 1
    tika-python

    tika-python

    Python binding to the Apache Tika™ REST services

    A Python port of the Apache Tika library that makes Tika available using the Tika REST Server. This makes Apache Tika available as a Python library, installable via Setuptools, Pip and easy to install. To use this library, you need to have Java 7+ installed on your system as tika-python starts up the Tika REST server in the background. To get this working in a disconnected environment, download a tika server file (both tika-server.jar and tika-server.jar.md5, which can be found here) and set...
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  • 2
    fastdup

    fastdup

    An unsupervised and free tool for image and video dataset analysis

    fastdup is a powerful free tool designed to rapidly extract valuable insights from your image & video datasets. Assisting you to increase your dataset images & labels quality and reduce your data operations costs at an unparalleled scale.
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  • 3
    crème de la crème of AI courses

    crème de la crème of AI courses

    This repository is a curated collection of links to various courses

    ...The project aggregates links to online courses, tutorials, lecture series, and learning materials from universities, research labs, and independent educators. The repository organizes courses by topic, difficulty level, format, and release year, allowing learners to quickly identify relevant material depending on their experience and interests. Topics covered include deep learning, natural language processing, computer vision, large language models, linear algebra, reinforcement learning, and machine learning engineering. Because the repository links to well-known educational content such as university lecture series and professional training materials, it functions as a structured roadmap for individuals who want to develop expertise in artificial intelligence.
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  • 4

    entity-metadata

    Lists of people, churches, and other entities

    Here are lists of entities, such as people, businesses, and churches. These are large files related to this repository https://github.com/az0/entity-metadata
    Downloads: 1 This Week
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  • 5
    Complete Machine Learning Package

    Complete Machine Learning Package

    A comprehensive machine learning repository containing 30+ notebooks

    Complete Machine Learning Package repository is a comprehensive educational collection of machine learning notebooks designed to teach core data science and AI concepts through practical coding examples. The project includes more than thirty notebooks that cover a wide range of topics including data analysis, statistical modeling, neural networks, and deep learning. Each notebook introduces theoretical ideas and then demonstrates how to implement them using Python libraries commonly used in...
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  • 6
    fe4ml-zh

    fe4ml-zh

    Feature Engineering for Machine Learning

    fe4ml-zh is an open-source project that provides a Chinese translation and structured documentation of the book Feature Engineering for Machine Learning. The repository aims to make advanced feature engineering concepts accessible to a broader audience by translating the content and organizing it into readable documentation and code examples. Feature engineering is a critical component of machine learning pipelines because it determines how raw data is transformed into features that...
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  • 7
    TensorFlow Ranking

    TensorFlow Ranking

    Learning to rank in TensorFlow

    TensorFlow Ranking is a library for Learning-to-Rank (LTR) techniques on the TensorFlow platform. Commonly used loss functions including pointwise, pairwise, and listwise losses. Commonly used ranking metrics like Mean Reciprocal Rank (MRR) and Normalized Discounted Cumulative Gain (NDCG). Multi-item (also known as groupwise) scoring functions. LambdaLoss implementation for direct ranking metric optimization. Unbiased Learning-to-Rank from biased feedback data. We envision that this library...
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  • 8
    Captcha Server

    Captcha Server

    A fast and stable captcha auto solving server with API.

    ...Launch Captcha Server from any Windows OS servers and set the server IP and Port to make it available to endusers and developers alike. Captcha Server has a very simple and straight forward API using the 2captcha.com API format. API is easy to fork and develop your own captcha business. Slash your captcha solving costs. Stop wasting your time and hard-earned money on captcha solving services that are slow, inaccurate and costly. Install Instructions - https://sourceforge.net/p/captchaserver/wiki/Install_Instructions/
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  • 9
    T81 558

    T81 558

    Applications of Deep Neural Networks

    Deep learning is a group of exciting new technologies for neural networks. Through a combination of advanced training techniques and neural network architectural components, it is now possible to create neural networks that can handle tabular data, images, text, and audio as both input and output. Deep learning allows a neural network to learn hierarchies of information in a way that is like the function of the human brain. This course will introduce the student to classic neural network...
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  • 10
    CodeContests

    CodeContests

    Large dataset of coding contests designed for AI and ML model training

    ...Each problem includes structured metadata, problem descriptions, paired input/output test cases, and multiple correct and incorrect solutions in various programming languages. The dataset is distributed in Riegeli format using Protocol Buffers, with separate training, validation, and test splits for reproducible machine learning experiments.
    Downloads: 2 This Week
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  • 11
    The fastai book

    The fastai book

    The fastai book, published as Jupyter Notebooks

    ...The code in the notebooks and python .py files is covered by the GPL v3 license; see the LICENSE file for details. The remainder (including all markdown cells in the notebooks and other prose) is not licensed for any redistribution or change of format or medium, other than making copies of the notebooks or forking this repo for your own private use. No commercial or broadcast use is allowed. We are making these materials freely available to help you learn deep learning, so please respect our copyright and these restrictions.
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  • 12
    Fashion-MNIST

    Fashion-MNIST

    A MNIST-like fashion product database

    Fashion-MNIST is an open-source dataset created by Zalando Research that provides a standardized benchmark for image classification algorithms in machine learning. The dataset contains grayscale images of fashion products such as shirts, shoes, coats, and bags, each labeled according to its clothing category. It was designed as a direct replacement for the original MNIST handwritten digits dataset, maintaining the same structure and image size so that researchers could easily switch datasets...
    Downloads: 4 This Week
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  • 13
    TensorFlow Backend for ONNX

    TensorFlow Backend for ONNX

    Tensorflow Backend for ONNX

    Open Neural Network Exchange (ONNX) is an open standard format for representing machine learning models. ONNX is supported by a community of partners who have implemented it in many frameworks and tools. TensorFlow Backend for ONNX makes it possible to use ONNX models as input for TensorFlow. The ONNX model is first converted to a TensorFlow model and then delegated for execution on TensorFlow to produce the output.
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  • 14
    BlazingSQL

    BlazingSQL

    BlazingSQL is a lightweight, GPU accelerated, SQL engine for Python

    BlazingSQL is a GPU-accelerated SQL engine built on top of the RAPIDS ecosystem. RAPIDS is based on the Apache Arrow columnar memory format, and cuDF is a GPU DataFrame library for loading, joining, aggregating, filtering, and otherwise manipulating data. BlazingSQL is a SQL interface for cuDF, with various features to support large-scale data science workflows and enterprise datasets.
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  • 15
    Sklearn TensorFlow

    Sklearn TensorFlow

    Sklearn and TensorFlow: A Practical Guide to Machine Learning

    Sklearn TensorFlow repository is an open-source project that provides a Chinese translation of the widely known book Hands-On Machine Learning with Scikit-Learn and TensorFlow. It aims to make practical machine learning education more accessible to Chinese-speaking learners by translating the technical explanations, examples, and exercises from the original English material. The repository organizes the content as structured documentation that can be compiled into multiple formats such as...
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  • 16
    Kashgari

    Kashgari

    Kashgari is a production-level NLP Transfer learning framework

    Kashgari is a simple and powerful NLP Transfer learning framework, build a state-of-art model in 5 minutes for named entity recognition (NER), part-of-speech tagging (PoS), and text classification tasks.
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  • 17
    Pytorch Points 3D

    Pytorch Points 3D

    Pytorch framework for doing deep learning on point clouds

    ...Core implementation of common components for point cloud deep learning - greatly simplifying the creation of new models. 4 Base Convolution base classes to simplify the implementation of new convolutions. Each base class supports a different data format.
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  • 18
    Universal Data Tool

    Universal Data Tool

    Collaborate & label any type of data, images, text, or documents etc.

    An open-source tool and library for creating and labeling datasets of images, audio, text, documents and video in an open data format. The Universal Data Tool can be used by anyone on your team, no data or programming skills needed. Simplicity without sacrificing any powerful developer features and integrations. Use the Universal Data Tool directly from a web browser or with a Windows, Mac or Linux desktop application. Join a link to a collaborative session and see dataset samples from team members complete in real-time. ...
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  • 19
    wav2letter++

    wav2letter++

    Facebook AI research's automatic speech recognition toolkit

    ...After installing, run export KENLM_ROOT_DIR=... so that wav2letter++ can find it. This is needed because KenLM doesn't support a make install step.wav2letter++ expects audio and transcription data to be prepared in a specific format so that they can be read from the pipelines. Each dataset (test/valid/train) needs to be in a separate file with one sample per line. A sample is specified using 4 columns separated by space (or tabs).
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  • 20
    GluonNLP

    GluonNLP

    NLP made easy

    ...Here are examples to evaluate the pre-trained embeddings included in the Gluon NLP toolkit as well as example scripts for training embeddings on custom datasets. Fasttext models trained with the library of Facebook research are exported both in text and a binary format. Unlike the text format, the binary format preserves information about subword units and consequently supports the computation of word vectors for words unknown during training (and not included in the text format). Besides training new fastText embeddings with Gluon NLP it is also possible to load the binary format into a Block provided by the Gluon NLP toolkit.
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  • 21
    Isolation Similarity

    Isolation Similarity

    aNNE similarity based on Isolation Kernel

    ...Nearest-neighbour-induced isolation similarity and its impact on density-based clustering. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 33, pp. 4755-4762). https://ojs.aaai.org//index.php/AAAI/article/view/4402 Bibtex format: @inproceedings{qin2019nearest, title={Nearest-neighbour-induced isolation similarity and its impact on density-based clustering}, author={Qin, Xiaoyu and Ting, Kai Ming and Zhu, Ye and Lee, Vincent CS}, booktitle={Proceedings of the AAAI Conference on Artificial Intelligence}, volume={33}, pages={4755--4762}, year={2019} }
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  • 22
    MMdnn

    MMdnn

    Tools to help users inter-operate among deep learning frameworks

    MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML. MMdnn is a comprehensive and cross-framework tool to convert, visualize and diagnose deep learning (DL) models. The "MM" stands for model management, and "dnn" is the acronym of deep neural network. We implement a universal converter to convert DL models between frameworks,...
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  • 23
    COCO Annotator

    COCO Annotator

    Web-based image segmentation tool for object detection & localization

    ...It provides many distinct features including the ability to label an image segment (or part of a segment), track object instances, label objects with disconnected visible parts, and efficiently store and export annotations in the well-known COCO format. The annotation process is delivered through an intuitive and customizable interface and provides many tools for creating accurate datasets. Several annotation tools are currently available, with most applications as a desktop installation. Once installed, users can manually define regions in an image and creating a textual description. ...
    Downloads: 1 This Week
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  • 24
    Magnitude

    Magnitude

    A fast, efficient universal vector embedding utility package

    A feature-packed Python package and vector storage file format for utilizing vector embeddings in machine learning models in a fast, efficient, and simple manner developed by Plasticity. It is primarily intended to be a simpler / faster alternative to Gensim but can be used as a generic key-vector store for domains outside NLP. It offers unique features like out-of-vocabulary lookups and streaming of large models over HTTP.
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  • 25
    Machine Learning cheatsheets Stanford

    Machine Learning cheatsheets Stanford

    VIP cheatsheets for Stanford's CS 229 Machine Learning

    stanford-cs-229-machine-learning is an open-source educational repository that provides illustrated cheat sheets summarizing the key concepts taught in Stanford University’s CS229 machine learning course. The project compiles concise explanations of important topics in machine learning and presents them in an accessible format that helps learners review complex ideas quickly. The repository includes summaries covering areas such as supervised learning, unsupervised learning, deep learning, and optimization techniques. In addition to machine learning algorithms, it also contains refresher materials on mathematical prerequisites including probability theory, statistics, linear algebra, and calculus. ...
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