Search Results for "modules" - Page 9
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Showing 259 open source projects for "modules"
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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DeepLearn
Implementation of research papers on Deep Learning+ NLP+ CV in Python
...This repository contains an implementation of the following research papers on NLP, CV, ML, and deep learning. The required dependencies are mentioned in requirement.txt. I will also use dl-text modules for preparing the datasets. If you haven't use it, please do have a quick look at it. CV, transfer learning, representation learning. -
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Toolbox
Piotr's Image & Video Matlab Toolbox
Piotr’s Image & Video MATLAB Toolbox is a general-purpose MATLAB toolbox for image and video processing and vision tasks, offering utilities, filters, detection, feature extraction, and algorithm building blocks. Example and demo scripts for usage (e.g. acfReadme, detector readmes). It augments MATLAB’s native capabilities (not replacing the Image Processing Toolbox) by providing efficient, reusable wrappers and optimized routines. Example and demo scripts for usage (e.g. acfReadme, detector... -
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Universe Starter Agent
A starter agent that can solve a number of universe environments
...Under the hood, this starter agent implements a version of the A3C (Asynchronous Advantage Actor-Critic) algorithm, adapted for the specific challenges of Universe environments (e.g., network latency, VNC streaming, asynchronous observations). The repo includes modules like train.py, worker.py, model.py, a3c.py, and envs.py to support training, parallel worker management, policy/critics, and environment wrappers. -
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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. -
Demo Series - Small Business Backup By VeeamWatch this on-demand demo series and learn how to protect your Microsoft 365 data with clear, simple, actionable steps that are easy to implement for businesses of all sizes.
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PyTorch Book
PyTorch tutorials and fun projects including neural talk
...But in theory there shouldn't be too many problems on python2 and CPU. The basic part (the first five chapters) explains the content of PyTorch. This part introduces the main modules in PyTorch and some tools commonly used in deep learning. For this part of the content, Jupyter Notebook is used as a teaching tool here, and readers can modify and run with notebooks and repeat experiments. -
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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 you. For users in China who may suffer from slow speeds when pulling the image from the public Docker registry, you can pull deepo images from the China registry mirror by specifying the full path, including the registry, in your docker pull command. This should work and enables Deepo to use the GPU from inside a docker container. -
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NNVM
Open deep learning compiler stack for cpu, gpu
The vision of the Apache NNVM Project is to host a diverse community of experts and practitioners in machine learning, compilers, and systems architecture to build an accessible, extensible, and automated open-source framework that optimizes current and emerging machine learning models for any hardware platform. Compilation of deep learning models into minimum deployable modules. Infrastructure to automatically generates and optimize models on more backend with better performance. Compilation and minimal runtimes commonly unlock ML workloads on existing hardware. Automatically generate and optimize tensor operators on more backends. Need support for block sparsity, quantization (1,2,4,8 bit integers, posit), random forests/classical ML, memory planning, MISRA-C compatibility, Python prototyping or all of the above? ... -
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Thalamus is a framework for creating modular interactive characters. Its goal is to make it possible to create interactive characters out of a set of different independent modules, each of which has a designated role in the behavior of the character. Unlike most the other interactive character frameworks, there is no specific module to act as the Mind, neither as the Body. It supports and is largely based on the architecture of SAIBA/BML. Acknowledgements: GAIPS/INESC-ID: (Intelligent Agents and Synthetic Characters Group) www.gaips.inesc-id.pt EMOTE: (Embodied Perceptive Tutors for Empathic Based Learning) www.emote-project.eu LIREC (LIving with Robots and Embodied Companions): www.lirec.eu
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The project supports the Welsh Language Technology domain with a set of NLP tools that drive innovation and advance the development of sophisticated textual analysis solutions. The WNLT project delivers four core NLP modules; a) Word Segmentation for separating text into words b) Sentence Boundary Disambiguation for finding sentence boundaries c) Part of Speech Tagger for determining the part of speech of each word d) Morphological Analyser for identifying the root form (lemma) of words. The modules are written in JAVA and ‘wrapped’ for execution under the General Architecture for Text Engineering (GATE) framework. ...
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Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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Welsh Natural Language Toolkit
WNLT is a suite of open source natural language modules for the Welsh
The project supports the Welsh Language Technology domain with a set of NLP tools that drive innovation and advance the development of sophisticated textual analysis solutions. The WNLT project delivers four core NLP modules; a) Word Segmentation for separating text into words b) Sentence Boundary Disambiguation for finding sentence boundaries c) Part of Speech Tagger for determining the part of speech of each word d) Morphological Analyser for identifying the root form (lemma) of words. The modules are written in JAVA and ‘wrapped’ for execution under the General Architecture for Text Engineering (GATE) framework. ... -
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DeepLearnToolbox
Matlab/Octave toolbox for deep learning
DeepLearnToolbox is a MATLAB / Octave toolbox for prototyping deep learning models. It provides implementations of feedforward neural networks, convolutional neural networks (CNNs), deep belief networks (DBNs), stacked autoencoders, convolutional autoencoders, and more. The toolbox includes example scripts for each method, enabling users to quickly experiment with architectures, training, and inference workflows. Although it's been flagged as deprecated and no longer actively maintained, it... -
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This package consists of Perl modules that implement the semantic relatedness measures of Leacock-Chodorow (1998), Jiang-Conrath (1997), Resnik (1995), Lin (1998), Hirst-St-Onge (1998), Wu & Palmer (1994), Banerjee-Pedersen (2002), and Patwardhan (2003).
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Aquila
Software Architecture for Cognitive Robotics
Aquila 2.0, an open-source cross-platform software architecture for cognitive robotics that makes use of independent heterogeneous CPU-GPU modules with loosely coupled dynamically generated graphical user interfaces. -
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SpecimenPhoto controls a Canon Powershot camera for specimen archival photography. Each photograph is assigned a case number, labeled and stored. Identification is manual or "hands free" using separately available barcode and speech recognition modules.
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Hydroponic Automation Platform (HAPI)
Technologies for automating food production on various scales
...High-yield production in urban settings is one of the primary goals. Artifacts include hardware design (mainly Arduino-based), firmware, management software and reporting modules. -
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ConvNetJS
Deep learning in Javascript to train convolutional neural networks
...No software requirements, no compilers, no installations, no GPUs, no sweat. ConvNetJS is an implementation of Neural networks, together with nice browser-based demos. It currently supports common Neural Network modules (fully connected layers, non-linearities), classification (SVM/Softmax) and Regression (L2) cost functions, ability to specify and train Convolutional Networks that process images, and experimental Reinforcement Learning modules, based on Deep Q Learning. The library allows you to formulate and solve Neural Networks in Javascript. ... -
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FineSplice
Enhanced splice junction detection and estimation from RNA-Seq data
...Multiple mapping reads with a unique location after filtering are rescued and reallocated to the most reliable candidate location. FineSplice requires Python 2.x (>= 2.6) with the following modules installed: pysam (http://code.google.com/p/pysam/) and scikit-learn (http://scikit-learn.org/). For further details check out our publication: Nucl. Acids Res. (2014) doi: 10.1093/nar/gku166 -
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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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PLC Programming
PLC Programming Best Practices
This project is for the development of PLC programming best practices. Based on expert input, a free video series will be developed by http://BIN95.com In this project we will start with the most basic 'start stop' ladder logic, then on to 'motor control' etc., working our way up to use of advanced instructions and tecniques. All along we will be using most common real world applications in PLC programming tutorial videos. -
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AReason
Artificial Reason Kernel and modules
Artificial Reason Kernel and modules -
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ajile
Advanced JavaScript Importing & Loading Extension
ajile: Advanced JavaScript Importing & Loading Extension allows developers to easily create unique namespaces for JavaScript modules and quickly define dependencies that allow scripts to automatically load and import each other as needed. -
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MACSY
Modular Architecture for Cognitive Systems
Macsy is a framework for developing modular agents. Data is organised in blackboards. Computations are performed by modules that annotate the data in the blackboards. Modules communicate indirectly through the annotations that they leave in the blackboards. The framework enables the development of decentralised software agents for a plethora of applications. -
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BADGr
Toolbox for Box Approximation, Decomposition, and Grasping
...The toolbox was developed in the Computer Vision & Active Perception Lab, at the Royal Institute of Technology, as a participant of the EU research project PACO-PLUS, and published at the project's end in Summer 2010. BADGr provides modules to approximate the shape of a point cloud (possibly from sensor data) by box primitives. These box primitives then serve as a base for the generation of box-based pre-grasp hypotheses for robot grippers. -
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ProLogic
Prolog wrapper for BWAPI
Enables Prolog developers to create AI modules for StarCraft BroodWar by wrapping the BWAPI functions in Prolog predicates. For more information refer to the Project Wiki.
