Search Results for "machine learning platform" - Page 17
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Showing 571 open source projects for "machine learning platform"
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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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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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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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TextTeaser
TextTeaser is an automatic summarization algorithm
...By combining these features with a simple scoring mechanism, it produces summaries that are both readable and informative. Originally inspired by research and earlier implementations, textteaser provides a lightweight solution for summarization without requiring heavy machine learning models. It is particularly useful for developers, researchers, or content platforms seeking a simple, rule-based approach to article summarization. -
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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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LocoKit
Location, motion, and activity recording framework for iOS
Machine Learning-based activity type detection. Improved detection of Core Motion activity types (stationary, walking, running, cycling, automotive). Distinguish between specific transport types (car, train, bus, motorcycle, airplane, boat). Optionally produce high level Path and Visit timeline items, to represent the recording session at human level. -
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Accord.NET Framework
Machine learning, computer vision, statistics and computing for .NET
...The Accord.NET project provides machine learning, statistics, artificial intelligence, computer vision and image processing methods to .NET. It can be used on Microsoft Windows, Xamarin, Unity3D, Windows Store applications, Linux or mobile. After merging with the AForge.NET project, the framework now offers a unified API for learning/training machine learning models that is both easy to use and extensible. -
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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... -
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Caffe2
Caffe2 is a lightweight, modular, and scalable deep learning framework
Caffe2 is a lightweight, modular, and scalable deep learning framework. Building on the original Caffe, Caffe2 is designed with expression, speed, and modularity in mind. Caffe2 is a deep learning framework that provides an easy and straightforward way for you to experiment with deep learning and leverage community contributions of new models and algorithms. You can bring your creations to scale using the power of GPUs in the cloud or to the masses on mobile with Caffe2’s cross-platform libraries. ... -
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Nanobox
The ideal platform for developers
Nanobox automates the creation of isolated, repeatable environments for local and production applications. When developing locally, Nanobox provisions your app's infrastructure inside of a virtual machine (VM) and mounts your local codebase into the VM. Any changes made to your codebase are reflected inside the virtual environment. Once code is built and tested locally, Nanobox provisions and deploys an identical infrastructure on a production platform. Nanobox uses Virtual Box and Docker to create virtual development environments on your local machine. ... -
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Accord.NET Framework
Scientific computing, machine learning and computer vision for .NET
The Accord.NET Framework provides machine learning, mathematics, statistics, computer vision, computer audition, and several scientific computing related methods and techniques to .NET. The project is compatible with the .NET Framework. NET Standard, .NET Core, and Mono. -
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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" -
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Eve
Better tools for thought
Eve is a programming language and IDE based on years of research into building a human-first programming platform. From code embedded in documents to a language without order, it presents an alternative take on what programming could be - one that focuses on us instead of the machine. We've made tremendous advancements since the early days of programming, but the modern form still forces us into the role of bit shifting machines. Programming has always been for us - the humans tapping at keyboards. ... -
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Skadoosh
A project that highly compresses android sources and uploads them here
Most Android platform developers have many problems, like slow internet or even low bandwidth. Due to this, they are unable to sync the big chunk of Android source codes from their respective repositories. Hence, most of the new and learning developers just fail at the first step which is downloading the source code! So, I started this project where people needing the sources just submit a pull request of they manifest required. -
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Caffe
A fast open framework for deep learning
Caffe is an open source deep learning framework that’s focused on expression, speed and modularity. It’s got an expressive architecture that encourages application and innovation, and extensible code that’s great for active development. Caffe also offers great speed, capable of processing over 60M images per day with a single NVIDIA K40 GPU. It’s arguably one of the fastest convnet implementations around. Caffe is developed by the Berkeley AI Research (BAIR)/The Berkeley Vision and... -
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Swift AI
The Swift machine learning library
Swift AI is a high-performance deep learning library written entirely in Swift. We currently offer support for all Apple platforms, with Linux support coming soon. Swift AI includes a collection of common tools used for artificial intelligence and scientific applications. A flexible, fully-connected neural network with support for deep learning. Optimized specifically for Apple hardware, using advanced parallel processing techniques. We've created some example projects to demonstrate the... -
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Grenade
Deep Learning in Haskell
Grenade is a composable, dependently typed, practical, and fast recurrent neural network library for concise and precise specifications of complex networks in Haskell. Because the types are so rich, there's no specific term level code required to construct this network; although it is of course possible and easy to construct and deconstruct the networks and layers explicitly oneself. Networks in Grenade can be thought of as a heterogeneous list of layers, where their type includes not only... -
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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. -
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Speakable Programming for Every Language
Your language to speak with all.
This project has the language data for spel, the main new codebase is at: https://gitlab.com/liberit/pyac A computer programming language using human language syntax for human-to-human and human-to-computer communication with high precision, supporting many languages. Currently has alpha prototype support for analytic versions of the UN languages English, Mandarin Chinese, Spanish, Arabic, Russian... -
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node2vec
Learn continuous vector embeddings for nodes in a graph using biased R
...The repository contains reference code accompanying the research paper node2vec: Scalable Feature Learning for Networks (KDD 2016). It allows researchers and practitioners to apply node2vec to various graph datasets and evaluate embedding quality on downstream tasks. By bridging ideas from graph theory and word embedding models, this project demonstrates how graph-based machine learning can be made efficient and flexible. -
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VCL4J - Free Pascal VCL 4 Java/Android
Develop Java/Android applications using FreePascal JVM & VCL4J
...This is an ALPHA release: https://en.wikipedia.org/wiki/Software_release_life_cycle#Alpha You can copy the installed files over to Linux and it should work. I'll be releasing a cross platform installer soon. Please contact me if you want to contribute. This is the start of what will most likely take a year to complete. I plan on writing a FCL/VCL style library in Pascal which will compile for the Java Virtual Machine (JVM) using FreePascal. Useful Links: Java https://java.com/en/download/ Lazarus https://sourceforge.net/projects/lazarus/ FreePascal JVM http://wiki.freepascal.org/FPC_JVM -
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nunn
This is an implementation of a machine learning library in C++17
nunn is a collection of ML algorithms and related examples written in modern C++17. -
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Rodeo
A data science IDE for Python
...Rodeo makes it very easy for its users to explore what is created by them and also alongside allows the users to Inspect, interact, compare data frames, plots and even much more. It is an IDE that has been built especially for data science/Machine Learning in Python and you can also very simply think of it as a light weight alternative to the IPython Notebook. -
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Random Bits Forest
RBF: a Strong Classifier/Regressor for Big Data
We present a classification and regression algorithm called Random Bits Forest (RBF). RBF integrates neural network (for depth), boosting (for wideness) and random forest (for accuracy). It first generates and selects ~10,000 small three-layer threshold random neural networks as basis by gradient boosting scheme. These binary basis are then feed into a modified random forest algorithm to obtain predictions. In conclusion, RBF is a novel framework that performs strongly especially on data... -
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GlobalSight
Open-source Translation Management System (TMS)
GlobalSight is an open-source Translation Management System (TMS) that provides a scalable translation management platform tailored for companies to manage, translate and deliver global content. Detailed release notes are available on our wiki. http://www.globalsight.com/wiki/index.php/GlobalSight_releases -
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JCLTP
A Java Class Library for Text Processing
JCLTP is a class library designed for processing text. JCLTP is free, open source and developed with the Java programming language. JCLTP is distributed under the GNU license. It incorporates several technologies that enable process information while applying AI techniques, in order to build predictive models for text classification. Through a flexible structure of interfaces and classes, the opportunity to extend, adapt and add functionality JCLTP is provided. Thus, analysis of new types...