Showing 106 open source projects for "deep learning with python"

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  • 1

    Botnet Detectors Comparer

    Compares botnet detection methods

    Compares botnet detection methods by computing the error metrics by reading the labels on a NetFlow file. The original NetFlow should have a new column for the ground-truth label, and a new column with the prediction label for each botnet detection method. This program computes all the error metrics (TPR, TNR, FPR, FNR, Precision, Accuracy, ErrorRate, FMeasure1, FMeasure2, FMeasure0.5) and output the comparison results. It also ouputs a png plot. The program can compare in a...
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  • 2

    ktree

    clustering, machine learning, algorithms

    This project has moved to github at http://lmwtree.devries.ninja.
    Downloads: 0 This Week
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  • 3
    This project develops a simple, fast and easy to use Python graph library using NumPy, Scipy and PySparse.
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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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  • 5

    ppc_sim_booke

    e500v2 simulator

    An experimental ISS for freescale's e500v2 core. It is meant to simulate only cpu and memory subsystem and is purely intended for academic/learning purposes only.
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  • 6
    A High-Order Multi-Variate Approximation Scheme for Arbitrary Data Sets, C implementation of the method described in http://web.mit.edu/qiqi/www/paper/interpolation.pdf, with Python and Fortran interfaces.
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  • 7
    MyNook

    MyNook

    A machine learning system for supervised document classification

    An open source system for supervised document classification based on statistical machine learning techniques. On the contrary of the state of art classification techniques, MyNook just requires the title of the document, not the content itself.
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  • 8
    JBoost is a simple, robust system for classification. JBoost contains implementations of several boosting algorithms in an alternating decision tree framework. In addition, JBoost provides extensible software for adding more learning algorithms.
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  • 9
    Redundancy due to cut-paste operations in text creates bias in machine learning for NLP. This module takes a directory and produces a subset of the files in that directory (in a list) with an upper bound on similarity between two files.
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  • 10
    mlpy

    mlpy

    Machine Learning Python

    ...mlpy is available both for Python >=2.6 and Python 3.X.
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  • 11
    Open Bayes is a python free/open library that allows users to easily create a bayesian network and perform inference/learning on it. It is mainly inspired from the Bayes Net Toolbox (BNT) but uses python as a base language. www.openbayes.org
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  • 12
    Platform for parallel computation in the Amazon cloud, including machine learning ensembles written in R for computational biology and other areas of scientific research. Home to MR-Tandem, a hadoop-enabled fork of X!Tandem peptide search engine.
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  • 13
    An agent-based situated language learning simulation that focuses on lexical learning and grounding, featuring a unigram syntax structure and a CFG-based semantic grammar. Created as a MSc thesis project, using python.
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  • 14
    Naimath (syn. blessing) is a project to create tools for diagnosis, management of clinical cases in the form of Rule based Medical Expert System integrating Interactive Health education, Semantified EMR, and serve as a learning tool for students. Website seen at www.naimath.com
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  • 15
    Monte is machine learning in pure Python. Monte's focus is the construction of gradient based learning machines from many small components.
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  • 16
    Hermetica is an educational tool for learning about logic. It functions partly as a proof checker with inline annotations. It will also support python scripting for automated subproofs and calculations. I would especially like help with the artwork.
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  • 17
    BCI Project Triathlon
    A three-step approach towards experimental brain-computer-interfaces, based on the OCZ nia device for EEG-data acquisition and artificial neural networks for signal-interpretation.
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  • 18
    This program generates customizable hyper-surfaces (multi-dimensional input and output) and samples data from them to be used further as benchmark for response surface modeling tasks or optimization algorithms.
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  • 19
    A Python function library to extract EEG feature from EEG time series in standard Python and numpy data structure. Features include classical spectral analysis, entropies, fractal dimensions, DFA, inter-channel synchrony and order, etc.
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  • 20
    A HTML scraper that uses machine learning frameworks to extract labelled fields from raw HTML. The project also involves the development of a tool to display the semi structured data generated by the scraper component.
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  • 21
    pygpr is a collection of algorithms that can be used to perform Gaussian process regression and global optimization.
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  • 22
    Python framework for video processing and content analysis using CUDA for acceleration.
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  • 23
    pyPal is a jabber based chatterbot that can be used to launch commands remotely as well as to make some good conversation. It is expected to be capable of multi-language learning.
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  • 24
    General purpose agents using reinforcement learning. Combines radial basis functions, temporal difference learning, planning, uncertainty estimations, and curiosity. Intended to be an out-of-the-box solution for roboticists and game developers.
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  • 25
    Net.py is a tool for learning about neural nets. Currently, it only allows the user to experiment with a Hopfield net. I am now extending it to cover the Kohonen net. I'd be pleased to receive suggestions and criticism.
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