Showing 127 open source projects for "file-studio"

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  • 1
    automl-gs

    automl-gs

    Provide an input CSV and a target field to predict, generate a model

    Give an input CSV file and a target field you want to predict to automl-gs, and get a trained high-performing machine learning or deep learning model plus native Python code pipelines allowing you to integrate that model into any prediction workflow. No black box: you can see exactly how the data is processed, and how the model is constructed, and you can make tweaks as necessary. automl-gs is an AutoML tool which, unlike Microsoft's NNI, Uber's Ludwig, and TPOT, offers a zero code/model definition interface to getting an optimized model and data transformation pipeline in multiple popular ML/DL frameworks, with minimal Python dependencies (pandas + scikit-learn + your framework of choice). automl-gs is designed for citizen data scientists and engineers without a deep statistical background under the philosophy that you don't need to know any modern data preprocessing and machine learning engineering techniques to create a powerful prediction workflow.
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  • 2
    brainCL_chung
    brainCL chung is a small program with dll to compute 3 to 4 layers neural networks with bulk training learn input data to bulk output data using openCL (cpu or gpu) acceleration written in easy fast freebasic
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  • 3
    Oryx

    Oryx

    Lambda architecture on Apache Spark, Apache Kafka for real-time

    ...It is a framework for building applications but also includes packaged, end-to-end applications for collaborative filtering, classification, regression and clustering. The application is written in Java, using Apache Spark, Hadoop, Tomcat, Kafka, Zookeeper and more. Configuration uses a single Typesafe Config config file, wherein applications configure an entire deployment of the system. This includes implementations of key interface classes which implement the batch, speed, and serving logic. Applications package and deploy their implementations with each instance of the layer binaries. Each of these is a runnable Java .jar which starts all necessary services.
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  • 4

    TensorImage

    Image classification library for easily training and deploying models

    ...TensorImage is easy to use and manage as all files, trained models and data are organized within a workspace directory, which you can change at any time in the configuration file, therefore being able have an indefinite amount of workspace directories for different purposes. Moreover, TensorImage can also be used to classify on thousands of images with trained image classification models.
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  • 5
    3D ResNets for Action Recognition

    3D ResNets for Action Recognition

    3D ResNets for Action Recognition (CVPR 2018)

    We uploaded the pretrained models described in this paper including ResNet-50 pretrained on the combined dataset with Kinetics-700 and Moments in Time. We significantly updated our scripts. If you want to use older versions to reproduce our CVPR2018 paper, you should use the scripts in the CVPR2018 branch.
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  • 6

    AerinSistemas-Noname

    Elasticsearch to Pandas dataframe or CSV

    API and command line utility, written in Python, for querying Elasticsearch exporting result as documents into a CSV file. The search can be done using logical operators or ranges, in combination or alone. The output can be limited to the desired attributes. Also ToT can insert the querying to a Pandas Dataframe or/and save its in a HDF5 container (under development).
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  • 7

    Face Recognition

    World's simplest facial recognition api for Python & the command line

    Face Recognition is the world's simplest face recognition library. It allows you to recognize and manipulate faces from Python or from the command line using dlib's (a C++ toolkit containing machine learning algorithms and tools) state-of-the-art face recognition built with deep learning. Face Recognition is highly accurate and is able to do a number of things. It can find faces in pictures, manipulate facial features in pictures, identify faces in pictures, and do face recognition on a...
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  • 8
    Batch File Artificial Intelligence

    Batch File Artificial Intelligence

    Chat bot and free roaming AI in batch

    Included in this project is a simple chat bot, a battle AI, and a swarm based free roaming AI.
    Downloads: 1 This Week
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  • 9
    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' argument in model constructor for all image models, weights='msd' for the music tagging model). ...
    Downloads: 1 This Week
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  • 10
    DeepLearningProject

    DeepLearningProject

    An in-depth machine learning tutorial

    This tutorial tries to do what most Most Machine Learning tutorials available online do not. It is not a 30 minute tutorial that teaches you how to "Train your own neural network" or "Learn deep learning in under 30 minutes". It's a full pipeline which you would need to do if you actually work with machine learning - introducing you to all the parts, and all the implementation decisions and details that need to be made. The dataset is not one of the standard sets like MNIST or CIFAR, you...
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  • 11

    Training Image Operators from Samples

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

    ...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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  • 12
    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 JASP for advanced data editing and RapidMiner for advanced prediction modeling. ...
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  • 13

    SPAWNN

    SPatial Analysis With self-organizing Neural Networks

    The SPAWNN toolkit is an innovative toolkit for spatial analysis with self-organizing neural networks which is particularily useful for spatial analysis, visualization and geographical data mining. To run the toolkit, simply download and execute (double-click) the jar-file. Please cite: - Hagenauer, J., & Helbich, M. (2016). SPAWNN: A Toolkit for SPatial Analysis With Self-Organizing Neural Networks. Transactions in GIS, 20(5), 755-775. Other related publications: - Hagenauer, J. (2016). Weighted merge context for clustering and quantizing spatial data with self-organizing neural networks. ...
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  • 14

    sgmweka

    Weka wrapper for the SGM toolkit for text classification and modeling.

    ...Has lower time complexity of classification than comparable software due to inference based on sparse model representation and use of an inverted index. The provided .zip file is in the Weka package format, giving access to text classification. Other functions are usable through either Java command-line commands or class inclusion into Java projects.
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    Downloads: 12 This Week
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  • 15
    ...The second package includes source and object files of DEMass-DBSCAN to be used with the WEKA system. 3. The third package DEMassBayes includes the source and object files of a Bayesian classifier using DEMass. DEMassBayes.7z has jar file to be used with WEKA and a readme file listing parameters used. The source files are included in DEMassBayes_Source.7z. 4. The four package is MassTER includes source and JAR file to be used with WEKA system..
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  • 16
    Adaptive Gaussian Filtering

    Adaptive Gaussian Filtering

    Machine learning with Gaussian kernels.

    Libagf is a machine learning library that includes adaptive kernel density estimators using Gaussian kernels and k-nearest neighbours. Operations include statistical classification, interpolation/non-linear regression and pdf estimation. For statistical classification there is a borders training feature for creating fast and general pre-trained models that nonetheless return the conditional probabilities. Libagf also includes clustering algorithms as well as comparison and validation...
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  • 17

    SuRankCo

    Supervised Ranking of Contigs in de novo Assemblies

    ...For more details about SuRankCo and its functioning, please see "SuRankCo: Supervised Ranking of Contigs in de novo Assemblies" Mathias Kuhring, Piotr Wojtek Dabrowski, Andreas Nitsche and Bernhard Y. Renard (http://www.biomedcentral.com/1471-2105/16/240/abstract) PLEASE NOTE, it is recommended to read the paper and the readme.txt file before using SuRankCo. Update Jun2015: * Minor changes to enable BAM support. Update Feb2014: * Added support for FASTA/SAM assemblies in addition to ACE/FASTQ(QUAL). NOTE: features of FASTA/SAM assemblies do not include BaseCount, BaseSeqmentCount and ContigQualities yet.
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  • 18
    Star Ships Learning Framework
    The Star Ships Learning Framework (SSLF) provides basic routines and methods in order to interact with the space shooter Star Ships V2.1. It provides the necessary interfaces for controlling the program's ships and its logic from outside the game.
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  • 19

    NeuroSolutions: Formula Generator

    Utility converts the weights file of a MLP Breadboard into a formula

    The NeuroSolutions: Formula Generator utility converts the weights file of a default MLP breadboard (1-hidden layer with a TanhAxon in the hidden layer and either a TanhAxon or BiasAxon in the output layer) into a usable formula that can be copied and pasted into your own programs to compute the output of the trained neural network.
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  • 20

    Genetic Algorithms Engine - Blackjack

    A genetic algortihm engine that evolves blackjack basic strategy.

    ...The genetic algorithm engine currently plays many blackjack hands for the fitness function and produces a result similar to blackjack basic strategy. To see it in action, download the zip file and run either: GABlackjack_Demo.exe     (quick)   or GABlackjack_Long.exe       (slow, but it achieves better results). The code was written in C++, using MS Visual Studio 6.0 and MS Visual Source Safe 6.0. The genetic algorithm engine supports various mutation rates, ranked parental selection, stochastic sampling parental selection, cyclic crossover, crossover at each gene, cloning the best individual each generation, and creating random individuals each generation. ...
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  • 21

    ANNFiD

    A forensic file identification tool using neural networks

    Just carved a bunch of bytes and have no idea what they could be? Maybe ANNFiD can help. ANNFiD uses neural network to identify byte patterns. It can be trained and has a GUI to help in the process. The tool is still on a very early stage, but could improve exponentially with the help of the developer community
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  • 22
    Flamingo Project

    Flamingo Project

    Workflow Designer, Hive Editor, Pig Editor, File System Browser

    Flamingo is a open-source Big Data Platform that combine a Ajax Rich Web Interface + Workflow Engine + Workflow Designer + MapReduce + Hive Editor + Pig Editor. 1. Easy Tool for big data 2. Use comfortable in Hadoop EcoSystem projects 3. Based GPL V3 License Supporting Pig IDE, Hive IDE, HDFS Browser, Scheduler, Hadoop Job Monitoring, Workflow Engine, Workflow Designer, MapReduce.
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  • 23
    Kernel Adaptive Filtering Toolbox

    Kernel Adaptive Filtering Toolbox

    a Matlab benchmarking toolbox for kernel adaptive filtering

    ...They are suitable for nonlinear filtering, prediction, tracking and nonlinear regression in general. This toolbox includes algorithms, demos, and tools to compare their performance. See the included README file for a list of included algorithms and more details. If you use this toolbox in your research please cite: @inproceedings{vanvaerenbergh2013comparative, author = {Van Vaerenbergh, Steven and Santamar{\'i}a, Ignacio}, booktitle = {2013 IEEE Digital Signal Processing (DSP) Workshop and IEEE Signal Processing Education (SPE)}, title = {A Comparative Study of Kernel Adaptive Filtering Algorithms}, year = {2013}, note = {Software available at \url{https://github.com/steven2358/kafbox/}} }
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  • 24
    neural network designer

    neural network designer

    a dbms for neural nets. Chatbots, DTrees, random forests, n-grams,...

    This project consists out of a windows based designer application and a library (that can run on multiple platforms, including android) together with several demo applications (including an MVC3 chatbot client and an android application). It is probably best compared to a database management system, but for neural networks instead of relational data. As such, the library is optimized for handling any type of data-size by using advanced streaming and caching algorithms. With the designer,...
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  • 25
    FineSplice

    FineSplice

    Enhanced splice junction detection and estimation from RNA-Seq data

    FineSplice is a Python wrapper to TopHat2 geared towards a reliable identification of expressed exon junctions from RNA-Seq data, at enhanced detection precision with small loss in sensitivity. Following alignment with TopHat2 using known transcript annotations, FineSplice takes as input the resulting BAM file and outputs a confident set of expressed splice junctions with the corresponding read counts. Potential false positives arising from spurious alignments are filtered out via a semi-supervised anomaly detection strategy based on logistic regression. Multiple mapping reads with a unique location after filtering are rescued and reallocated to the most reliable candidate location. ...
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