Showing 1025 open source projects for "machine"

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  • 1
    WireFactory Simulator

    WireFactory Simulator

    Small factory simulator for control logic test purpose

    Wire Factory Simulator (WFS) is a free software to simulate the control of a factory, mainly controlled by IEC 61499 applications. You can build your own factory and controller. The controller can be implemented on any programming language. WFS was originally built to simulate the action of an IEC 614999 application. So, the devices in the factory are easily connected to IEC 61499 applications. The WFS were mainly tested with FBDK (http://www.holobloc.com/). Wire Factory has been...
    Downloads: 1 This Week
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  • 2
    PyTorch Book

    PyTorch Book

    PyTorch tutorials and fun projects including neural talk

    This is the corresponding code for the book "The Deep Learning Framework PyTorch: Getting Started and Practical", but it can also be used as a standalone PyTorch Getting Started Guide and Tutorial. The current version of the code is based on pytorch 1.0.1, if you want to use an older version please git checkout v0.4or git checkout v0.3. Legacy code has better python2/python3 compatibility, CPU/GPU compatibility test. The new version of the code has not been fully tested, it has been tested...
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  • 3
    Image classification models for Keras

    Image classification models for Keras

    Keras code and weights files for popular deep learning models

    All architectures are compatible with both TensorFlow and Theano, and upon instantiation the models will be built according to the image dimension ordering set in your Keras configuration file at ~/.keras/keras.json. For instance, if you have set image_dim_ordering=tf, then any model loaded from this repository will get built according to the TensorFlow dimension ordering convention, "Width-Height-Depth". Pre-trained weights can be automatically loaded upon instantiation (weights='imagenet'...
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  • 4
    Intel neon

    Intel neon

    Intel® Nervana™ reference deep learning framework

    neon is Intel's reference deep learning framework committed to best performance on all hardware. Designed for ease of use and extensibility. See the new features in our latest release. We want to highlight that neon v2.0.0+ has been optimized for much better performance on CPUs by enabling Intel Math Kernel Library (MKL). The DNN (Deep Neural Networks) component of MKL that is used by neon is provided free of charge and downloaded automatically as part of the neon installation. The gpu...
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  • 5
    Tangent

    Tangent

    Source-to-source debuggable derivatives in pure Python

    ...In contrast, Tangent performs ahead-of-time autodiff on the Python source code itself, and produces Python source code as its output. Tangent fills a unique location in the space of machine learning tools. As a result, you can finally read your automatic derivative code just like the rest of your program. Tangent is useful to researchers and students who not only want to write their models in Python, but also read and debug automatically-generated derivative code without sacrificing speed and flexibility. Tangent works on a large and growing subset of Python, provides extra autodiff features other Python ML libraries don't have, has reasonable performance, and is compatible with TensorFlow and NumPy.
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  • 6
    Five video classification methods

    Five video classification methods

    Code that accompanies my blog post outlining five video classification

    Classifying video presents unique challenges for machine learning models. As I’ve covered in my previous posts, video has the added (and interesting) property of temporal features in addition to the spatial features present in 2D images. While this additional information provides us more to work with, it also requires different network architectures and, often, adds larger memory and computational demands.We won’t use any optical flow images.
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  • 7
    Deepo

    Deepo

    Set up deep learning environment in a single command line

    Deepo is a series of Docker images that allows you to quickly set up your deep learning research environment, supports almost all commonly used deep learning frameworks, supports GPU acceleration (CUDA and cuDNN included), also works in CPU-only mode, and works on Linux (CPU version/GPU version), Windows (CPU version) and OS X (CPU version). Their Dockerfile generator that allows you to customize your own environment with Lego-like modules, and automatically resolves the dependencies for...
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  • 8
    Machine Learning for OpenCV

    Machine Learning for OpenCV

    M. Beyeler (2017). Machine Learning for OpenCV

    M. Beyeler (2017). Machine Learning for OpenCV: Intelligent image processing with Python. Packt Publishing Ltd., ISBN 978-178398028-4.
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  • 9
    AI learning

    AI learning

    AiLearning, data analysis plus machine learning practice

    We actively respond to the Research Open Source Initiative (DOCX) . Open source today is not just open source, but datasets, models, tutorials, and experimental records. We are also exploring other categories of open source solutions and protocols. I hope you will understand this initiative, combine this initiative with your own interests, and do what you can. Everyone's tiny contributions, together, are the entire open source ecosystem. We are iBooker, a large open-source community,...
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  • 10
    A Complete Beginner's Guide to Django

    A Complete Beginner's Guide to Django

    A Complete Beginner's Guide to Django - Code Samples

    Code samples from the Django tutorial series. I’m starting a new tutorial series about Django fundamentals. It’s a complete beginner’s guide to start learning Django. The material is divided into seven parts. We’re going to explore all the basic concepts in great detail, from installation, and preparation of the development environment, models, views, templates, URLs to more advanced topics such as migrations, testing, and deployment. I wanted to do something different. A tutorial that would...
    Downloads: 1 This Week
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  • 11
    auto_ml

    auto_ml

    Automated machine learning for analytics & production

    auto_ml is designed for production. Here's an example that includes serializing and loading the trained model, then getting predictions on single dictionaries, roughly the process you'd likely follow to deploy the trained model. Before you go any further, try running the code. Load up some data (either a DataFrame, or a list of dictionaries, where each dictionary is a row of data). Make a column_descriptions dictionary that tells us which attribute name in each row represents the value we’re...
    Downloads: 0 This Week
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  • 12
    Pootle Django

    Pootle Django

    Online translation tool

    ...Ensures the best quality localizations by automatically detecting common errors made by translators. Integrates user suggestions, terminology, Translation Memory, Machine Translation, and more. A number of translation projects for a number of languages can be hosted on Pootle. Teams can manage their files, permissions, projects, and translate on-line. Files can be downloaded for offline translation. Delegate to your translators and allow them to commit directly to your version control systems. Pootle can easily be adapted and integrated into your existing web look and feel.
    Downloads: 0 This Week
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  • 13
    multiplierz
    Open-source Python software library and GUI desktop environment for direct bioinformatic analysis of mass-spectrometry data through powerful scripting tools and interfaces to many machine data formats, database search engines, and peptide data formats. For a copy of the source code, check out our Github repositories: mzDesktop: https://github.com/MaxAlex/mzDesktop multiplierz: https://github.com/MaxAlex/multiplierz
    Downloads: 0 This Week
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  • 14
    Deep Learning with Keras and Tensorflow

    Deep Learning with Keras and Tensorflow

    Introduction to Deep Neural Networks with Keras and Tensorflow

    Introduction to Deep Neural Networks with Keras and Tensorflow. To date tensorflow comes in two different packages, namely tensorflow and tensorflow-gpu, whether you want to install the framework with CPU-only or GPU support, respectively. NVIDIA Drivers and CuDNN must be installed and configured before hand. Please refer to the official Tensorflow documentation for further details. Since version 0.9 Theano introduced the libgpuarray in the stable release (it was previously only available in...
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  • 15
    ctrax
    Ctrax is a machine vision program for estimating the positions and orientations of many walking fruit flies, maintaining their individual identities over long periods of time with minimal supervision, and on average for 1.5 fly-hours automatically.
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    Downloads: 32 This Week
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  • 16

    Chronological Cohesive Units

    The experimental source code for the paper

    The experimental source code for the paper, "A Novel Recommendation Approach Based on Chronological Cohesive Units in Content Consuming"
    Downloads: 0 This Week
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  • 17
    Lip Reading

    Lip Reading

    Cross Audio-Visual Recognition using 3D Architectures

    The input pipeline must be prepared by the users. This code is aimed to provide the implementation for Coupled 3D Convolutional Neural Networks for audio-visual matching. Lip-reading can be a specific application for this work. Audio-visual recognition (AVR) has been considered as a solution for speech recognition tasks when the audio is corrupted, as well as a visual recognition method used for speaker verification in multi-speaker scenarios. The approach of AVR systems is to leverage the...
    Downloads: 4 This Week
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  • 18
    Seq2seq Chatbot for Keras

    Seq2seq Chatbot for Keras

    This repository contains a new generative model of chatbot

    ...The data were collected from dialogues of English courses online. This trained model can be fine-tuned using a closed-domain dataset to real-world applications. The canonical seq2seq model became popular in neural machine translation, a task that has different prior probability distributions for the words belonging to the input and output sequences since the input and output utterances are written in different languages. The architecture presented here assumes the same prior distributions for input and output words. Therefore, it shares an embedding layer (Glove pre-trained word embedding) between the encoding and decoding processes through the adoption of a new model.
    Downloads: 0 This Week
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  • 19
    TensorFlow on Raspberry Pi

    TensorFlow on Raspberry Pi

    TensorFlow for Raspberry Pi

    TensorFlow on Raspberry Pi.
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  • 20
    Py-backwards

    Py-backwards

    Python to python compiler that allows you to use Python 3.6 features

    py-backwards is a transpiler that takes modern Python code (with newer syntax) and converts it to older Python versions so you can run it in legacy environments. For example, if you want to use f-strings, type annotations, or other Python 3.x niceties but have to deploy on a machine that only has an older interpreter, py-backwards rewrites your code to an equivalent, earlier syntax. It does this by parsing the source into an abstract syntax tree (AST), applying transformation rules, and emitting compatible code. This allows teams to write forward-looking Python without immediately upgrading all their runtime environments. ...
    Downloads: 0 This Week
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  • 21

    Training Image Operators from Samples

    Tools to train Image Operators automatically from a set of samples.

    TRIOS - Training Image Operators from Samples is a set of tools to bring Image Processing closer to scientists in general. It is capable of estimating an operator between two images using only pairs of samples that contain an input image and the desired output. The operator is saved to a file and can be applied to any image.
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  • 22
    DSTK - DataScience ToolKit

    DSTK - DataScience ToolKit

    DSTK - DataScience ToolKit for All of Us

    DSTK - DataScience ToolKit is an opensource free software for statistical analysis, data visualization, text analysis, and predictive analytics. Newer version and smaller file size can be found at: https://sourceforge.net/projects/dstk3/ It is designed to be straight forward and easy to use, and familar to SPSS user. While JASP offers more statistical features, DSTK tends to be a broad solution workbench, including text analysis and predictive analytics features. Of course you may specify...
    Downloads: 5 This Week
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  • 23
    seq2seq

    seq2seq

    A general-purpose encoder-decoder framework for Tensorflow

    seq2seq is an early, influential TensorFlow reference implementation for sequence-to-sequence learning with attention, covering tasks like neural machine translation, summarization, and dialogue. It packaged encoders, decoders, attention mechanisms, and beam search into a modular training and inference framework. The codebase showcased best practices for batching, bucketing by sequence length, and handling variable-length sequences efficiently on GPUs. Researchers used it as a baseline to reproduce classic results and to prototype new attention variants and training tricks. ...
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  • 24
    Scattertext 0.2.1

    Scattertext 0.2.1

    Beautiful visualizations of how language differs among document types

    A tool for finding distinguishing terms in corpora and displaying them in an interactive HTML scatter plot. Points corresponding to terms are selectively labeled so that they don't overlap with other labels or points.
    Downloads: 0 This Week
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  • 25

    PyDaMelo

    Python-compatible Data mining elementary objects

    An attempt at offering machine learning and data mining algorithms at the finest grain we are able to, easy to combine together through Python scripting to glue together the Lego-like bricks.
    Downloads: 0 This Week
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