Search Results for "model-builder" - Page 69
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Showing 1978 open source projects for "model-builder"
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EvalAI
Evaluating state of the art in AI
...EvalAI lets participants submit code for their agent in the form of docker images which are evaluated against test environments on the evaluation server. During the evaluation, the worker fetches the image, test environment, and model snapshot and spins up a new container to perform the evaluation. -
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Vaex
Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python
...Vaex uses memory mapping, zero memory copy policy and lazy computations for best performance (no memory wasted). Cut development cut development time by 80%. Your prototype is your solution. Create automatic pipelines for any model. -
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GDeps
Automatic process to update and build your external libraries/projects
Welcome to GDeps! ( http://gdeps.org ) ========== [PRE-ALPHA] GDeps is a C++ dependencies/projects builder. Write in Python3. Launch a project script and GDeps will: 1) Create and Update the repository (svn, git, mercurial) 2) Make the solution (cmake, boost, bakefile) 3) Build the solution (Compilers : Mingw, VC90~140, Clang, Digital Mars, Ides : Visual Studio, Codeblocks ). Install: ========== 1) Install Python3: https://www.python.org/ 2) Install GDeps: https://sourceforge.net/projects/gdeps/files/latest/download?... -
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Siamese and triplet learning
Siamese and triplet networks with online triplet mining in PyTorch
...It includes data loaders, training scripts, neural network architectures, and evaluation metrics that allow researchers to experiment with different embedding learning strategies. The project also implements online pair and triplet mining techniques to efficiently generate training examples during model training. -
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tacotron
A TensorFlow Implementation of Tacotron
...It converts text into speech by learning acoustic representations and attention-based alignments from paired text and audio. The repository includes preprocessing, model modules, training, evaluation, and synthesis scripts. Example training setups use LJ Speech, Nick Offerman audiobook recordings, and the World English Bible dataset. Users can monitor loss and attention plots during training to evaluate alignment quality. Pretrained checkpoints and generated samples are provided as references for reproducing or studying the model's behavior. -
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pyhanlp
Chinese participle
...It is especially useful when you need a pragmatic “get results quickly” NLP layer for segmentation, tagging, entity extraction, parsing, or keyword-style tasks rather than experimenting with model training from scratch. -
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SCRAM
Probabilistic Risk Assessment Tool
SCRAM is a free and open source probabilistic risk analysis tool. The tool is under development to include fault tree, event tree, common cause, and other standard analyses. -
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Qutranpy
Interactive electronic quantum transport
Interactive program to perform quantum transport calculations by means of the Landauer and scattering matrix formalism, in a two terminal geometry. The Hamiltonians of leads and scattering region can be modified, adding exchange fields, mass, spin-orbit coupling or superconductivity. -
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The Deep Review
A collaboratively written review paper on deep learning, genomics, etc
This repository is home to the Deep Review, a review article on deep learning in precision medicine. The Deep Review is collaboratively written on GitHub using a tool called Manubot (see below). The project operates on an open contribution model, welcoming contributions from anyone. To see what's incoming, check the open pull requests. For project discussion and planning see the Issues. As of writing, we are aiming to publish an update of the deep review. We will continue to make project preprints available on bioRxiv or another preprint service and aim to continue publishing the finished reviews in a peer-reviewed venue as well. ... -
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RaspberryPi_LedSign
Python code drive PT6961 Led Sign AH41-01158A
This Simple project demonstrates how to send command and data to a PT6961 LED driver with a RaspberryPi by using Python. The Led Sign board (AH41-01158A) has been taken from an old Home Theater. A RaspberryPi model B has been used to communicate with. This code will ask the user to enter a sentence and will display this sentence 4 times. -
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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). Weights are automatically downloaded if necessary, and cached locally in ~/.keras/models/. ... -
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PassGAN
A Deep Learning Approach for Password Guessing
PassGAN is a research implementation of a generative adversarial network trained to model human password patterns. It reproduces ideas from the paper “PassGAN: A Deep Learning Approach for Password Guessing” using a modified Wasserstein GAN implementation. The repository includes scripts for training models and generating candidate password samples from learned distributions. A pretrained model based on the RockYou dataset is provided for reproducing experiments. -
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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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PyMathProg
An easy and flexible mathematical programming environment for Python.
PyMathProg is a Python reincarnation of AMPL and GNU MathProg modeling language, implemented in pure Python, connecting to GLPK via swiglpk. Create, optimize, report, change and re-optimize your model with Python, easily integrate database, plotting, etc. -
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BlockSparse
Efficient GPU kernels for block-sparse matrix multiplication
The blocksparse repository provides efficient GPU kernels (TensorFlow custom ops) for block-sparse matrix multiplication and convolution operations. The idea is to exploit block-level sparsity — i.e. treat matrices or weight tensors as composed of blocks, many of which may be zero or unused — to save compute and memory when sparsity patterns are structured. This is particularly useful in models like Sparse Transformers, where attention matrices or intermediate layers may adopt block-sparse... -
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Rekall
Rekall Memory Forensic Framework
...Extensibility is a core theme, with a plugin API and notebook-friendly workflows for custom hunts and triage. Used well, it compresses what would be hours of manual sleuthing into scripted passes over a consistent object model. -
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DualTranscriptDiscovery
Transcript-discovery approach for gene feature delimitation by RNA-seq
This project contains Python scripts usable for a dual transcript-discovery approach that improves the delimitation of gene features from RNA-seq data in the chicken model. Documentation: http://bio.biologists.org/content/biolopen/suppl/2018/01/17/bio.028498.DC1/BIO028498supp.pdf Citation: Orgeur M., Martens M., Börno S. T., Timmermann B., Duprez D. and Stricker S. (2018). A dual transcript-discovery approach to improve the delimitation of gene features from RNA-seq data in the chicken model. ... -
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trnsys-fmu
The FMI++ TRNSYS FMU Export Utility
...Instructions on installation and usage are given in the documentation, which is provided as part of the download. This documentation also contains a tutorial on how to export a TRNSYS model as FMU for co-simulation and how to link it with a simple controller implemented in Modelica. The tool is based on code from the FMI++ library. -
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pydictor
powerful and useful hacker dictionary builder for a brute-force attack
A powerful and useful hacker dictionary builder for a brute-force attack. You can use pydictor to generate a general blast wordlist, a custom wordlist based on Web content, a social engineering wordlist, and so on; You can use the pydictor built-in tool to safe delete, merge, unique, merge and unique, count word frequency to filter the wordlist, besides, you also can specify your wordlist and use '-tool handler' to filter your wordlist. -
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Five video classification methods
Code that accompanies my blog post outlining five video classification
...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. This reduces model complexity, training time, and a whole whack load of hyperparameters we don’t have to worry about. Every video will be subsampled down to 40 frames. So a 41-frame video and a 500-frame video will both be reduced to 40 frames, with the 500-frame video essentially being fast-forwarded. We won’t do much preprocessing. A common preprocessing step for video classification is subtracting the mean, but we’ll keep the frames pretty raw from start to finish. -
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ABC-SysBio implements likelihood free parameter inference and model selection in dynamical systems. It is designed to work with both stochastic and deterministic models written in Systems Biology Markup Language (SBML).
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wordvectors
Pre-trained word vectors of 30+ languages
...Scripts are included for corpus creation and for training new embeddings with either supported algorithm. Available languages include Chinese, Japanese, Korean, Spanish, French, German, Hindi, Russian, Vietnamese, Thai, and many others, with model metadata covering vector, corpus, and vocabulary sizes. -
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Seq2Seq Chatbot
Chatbot in 200 lines of code using TensorLayer
Seq2Seq Chatbot is an implementation of a sequence-to-sequence chatbot model using TensorLayer, demonstrating how to build conversational agents with minimal code. -
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cnn-benchmarks
Benchmarks for popular CNN models
...The repository includes scripts for running benchmarks on various architectures and datasets, making it easy to gather comparative metrics. By simplifying performance evaluation, it helps developers make informed decisions about model design and hardware selection. Overall, cnn-benchmarks is a practical tool for performance analysis in deep learning workflows. -
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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 trying to predict. ...
