Search Results for "virtual-machine" - Page 9
Sort By:
Showing 360 open source projects for "virtual-machine"
View related business solutions-
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.
-
$300 Free Credits to Build on Google CloudPut your $300 in credit toward real workloads, then keep building with free monthly usage for 20+ products. No commitment and no charge until you upgrade.
-
1
earthengine-py-notebooks
A collection of 360+ Jupyter Python notebook examples
earthengine-py-notebooks is a comprehensive collection of hundreds of Jupyter Python notebooks that serve as examples and tutorials for using the Google Earth Engine Python API. These notebooks are organized into thematic areas such as image processing, machine learning, visualization, filtering, and asset management, exposing users to real geospatial analysis tasks. The repository makes it easier to explore Earth Engine’s large geospatial data catalog, interactively display map layers, and generate visual insights without the need for external GIS software by leveraging interactive widgets and mapping libraries. ... -
2
Brain AutoML
Google Brain AutoML
This repository contains a list of AutoML related models and libraries. Google Brain researchers have introduced a new way of programming automated machine learning (AutoML) based on symbolic programming. The researchers also proposed PyGlove, a general symbolic programming library for Python, to implement the symbolic formulation of AutoML. AutoML, designed to fill the machine learning industry’s talent gap, is gaining traction among various organizations. -
3
GUI-lite
The smallest header-only GUI library(4 KLOC) for all platforms
...Code Telemetry and Analysis in real-time (remove .sh/.bat files if dislike sharing). Even a C beginner could master GUI-lite quickly. The source code only uses basic C++ features (class, virtual function). We chose C++ as it could make the code size significantly smaller and easier to read. Work smoothly with 3rd party frameworks(Qt/MFC/Winform/Cocoa/Web). Zero dependency, 100% build pass & runnable. Click the demo you like, and run it on your hardware. -
4
LevelDB
A fast key-value storage library
LevelDB is a library of persistent key values. Written at Google, it contains keys and values that are arbitrary byte arrays, ordered within the key value store according to a user-specified comparator function. LevelDB is not an SQL database and does not support SQL queries or indexes. It simply provides an ordered mapping from string keys to string values. Data is stored already sorted by key, though callers can override the sort order through a custom comparison function. It supports... -
Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
-
5
Superfine
Absolutely minimal view layer for building web interfaces
...When describing how a page looks in Superfine, we don't write markup. Instead, we use the h() and text() functions to create a lightweight representation of the DOM (or virtual DOM for short), and patch() to actually render the DOM. Superfine won't re-create the entire DOM every time we use patch(). By comparing the old and new virtual DOM we are able to change only the parts of the DOM that need to change instead of rendering everything from scratch. -
6
accessible-slick
The last (accessible) carousel you'll ever need
A highly accessible, WCAG 2.0 / 2.1 compliant, drop-in replacement for Slick Slider (1.8.1) crafted and tested by expert users and professional accessibility consultants, intended to make life easier for real-world dev teams who need to pass accessibility audits. -
7
OpenPose
Real-time multi-person keypoint detection library for body, face, etc.
OpenPose has represented the first real-time multi-person system to jointly detect human body, hand, facial, and foot keypoints (in total 135 keypoints) on single images. It is authored by Ginés Hidalgo, Zhe Cao, Tomas Simon, Shih-En Wei, Yaadhav Raaj, Hanbyul Joo, and Yaser Sheikh. It is maintained by Ginés Hidalgo and Yaadhav Raaj. OpenPose would not be possible without the CMU Panoptic Studio dataset. We would also like to thank all the people who has helped OpenPose in any way. 15, 18 or... -
8
gradslam
gradslam is an open source differentiable dense SLAM library
gradslam is an open-source framework providing differentiable building blocks for simultaneous localization and mapping (SLAM) systems. We enable the usage of dense SLAM subsystems from the comfort of PyTorch. The question of “representation” is central in the context of dense simultaneous localization and mapping (SLAM). Newer learning-based approaches have the potential to leverage data or task performance to directly inform the choice of representation. However, learning representations... -
9
NLP Architect
A model library for exploring state-of-the-art deep learning
NLP Architect is an open-source Python library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language Processing and Natural Language Understanding neural networks. The library includes our past and ongoing NLP research and development efforts as part of Intel AI Lab. NLP Architect is designed to be flexible for adding new models, neural network components, data handling methods, and for easy training and running models. NLP Architect is a... -
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.
-
10
TFLearn
Deep learning library featuring a higher-level API for TensorFlow
TFlearn is a modular and transparent deep learning library built on top of Tensorflow. It was designed to provide a higher-level API to TensorFlow in order to facilitate and speed up experimentations while remaining fully transparent and compatible with it. Easy-to-use and understand high-level API for implementing deep neural networks, with tutorials and examples. Fast prototyping through highly modular built-in neural network layers, regularizers, optimizers, and metrics. Full transparency... -
11
Encode_LV
LabVIEW VIs for ZLib compression and Base64/binhex encoding
These VIs use C-based DLL access to ZLib (https://zlib.net/) and ASCII encode/decode. The VIs and development files are included in this package. You are most likely to be running this from a Windows machine which means that loading the LabVIEW code will generate an error. This is due to the LabVIEW code pointing to the Linux SO instead of the DLL. To fix it, double-click on the CLFN VIs and browse to DLL. -
12
fastNLP
fastNLP: A Modularized and Extensible NLP Framework
fastNLP is a lightweight framework for natural language processing (NLP), the goal is to quickly implement NLP tasks and build complex models. A unified Tabular data container simplifies the data preprocessing process. Built-in Loader and Pipe for multiple datasets, eliminating the need for preprocessing code. Various convenient NLP tools, such as Embedding loading (including ELMo and BERT), intermediate data cache, etc.. Provide a variety of neural network components and recurrence models... -
13
SageMaker MXNet Training Toolkit
Toolkit for running MXNet training scripts on SageMaker
...With the SDK, you can train and deploy models using popular deep learning frameworks Apache MXNet and TensorFlow. You can also train and deploy models with Amazon algorithms, which are scalable implementations of core machine learning algorithms that are optimized for SageMaker and GPU training. If you have your own algorithms built into SageMaker compatible Docker containers, you can train and host models using these as well. -
14
Dart
Dart is a client-optimized language for fast apps on any platform
...Develop with a programming language specialized around the needs of user interface creation. Make changes iteratively, use hot reload to see the result instantly in your running app. Compile to ARM & x64 machine code for mobile, desktop, and backend. Or compile to JavaScript for the web. Mature and complete async-await for user interfaces containing event-driven code, paired with isolate-based concurrency. A programming language optimized for building user interfaces with features such as sound null safety, the spread operator for expanding collections, and collection if for customizing UI for each platform. ... -
15
MMdnn
Tools to help users inter-operate among deep learning frameworks
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML. MMdnn is a comprehensive and cross-framework tool to convert, visualize and diagnose deep learning (DL) models. The "MM" stands for model management, and "dnn" is the acronym of deep neural network. We implement a universal converter to convert DL models between frameworks,... -
16
Forecasting Best Practices
Time Series Forecasting Best Practices & Examples
Time series forecasting is one of the most important topics in data science. Almost every business needs to predict the future in order to make better decisions and allocate resources more effectively. This repository provides examples and best practice guidelines for building forecasting solutions. The goal of this repository is to build a comprehensive set of tools and examples that leverage recent advances in forecasting algorithms to build solutions and operationalize them. Rather than... -
17
AdaNet
Fast and flexible AutoML with learning guarantees
AdaNet is a TensorFlow framework for fast and flexible AutoML with learning guarantees. AdaNet is a lightweight TensorFlow-based framework for automatically learning high-quality models with minimal expert intervention. AdaNet builds on recent AutoML efforts to be fast and flexible while providing learning guarantees. Importantly, AdaNet provides a general framework for not only learning a neural network architecture but also for learning to the ensemble to obtain even better models. At each... -
18
Euler
A distributed graph deep learning framework.
As a general data structure with strong expressive ability, graphs can be used to describe many problems in the real world, such as user networks in social scenarios, user and commodity networks in e-commerce scenarios, communication networks in telecom scenarios, and transaction networks in financial scenarios. and drug molecule networks in medical scenarios, etc. Data in the fields of text, speech, and images is easier to process into a grid-like type of Euclidean space, which is suitable... -
19
Wheefun Emulator Framework
A framework for developing emulators
...It was originally designed to support the WDMF project, which has need for hardware emulation on modern operating systems. However, it could conceivably be used in other projects. At its core, WFEF provides primitives for emulating a generic system bus and for providing access to virtual screens, sound, and input management. From this, a variety of hardware can be virtualized. We aim to also provide hardware emulation for specific commonly used hardware. As game developers are likely to use this software, it is licensed under the GPL V3 with the Classpath Exception. Providers for certain functionality which may only be accessible under NDA (such as for game consoles) may be afforded by externally linking an implementation. -
20
usbmuxd
A socket daemon to multiplex connections from and to iOS devices
...Alternatively, just pass a different username using the -U argument. usbmuxd is not used for tethering data transfers which uses a dedicated USB interface to act as a virtual network device. The higher-level layers, especially if you want to write an application to interact with the device, are handled by libimobiledevice. -
21
ocapi
C-level driver collection for MSP430 and derivatives
...So it should work, no matter if you live in the Windows, Linux or Mac world. ocapi is used as the hardware abstraction layer for the MSP430 port of the Takatuka Java virtual machine (JVM). Before it can be used, the library must be built from the sources provided here. The build environment allows for fine grained configuration of the library's functionality and target system. -
22
Tensor2Tensor
Library of deep learning models and datasets
Deep Learning (DL) has enabled the rapid advancement of many useful technologies, such as machine translation, speech recognition and object detection. In the research community, one can find code open-sourced by the authors to help in replicating their results and further advancing deep learning. However, most of these DL systems use unique setups that require significant engineering effort and may only work for a specific problem or architecture, making it hard to run new experiments and compare the results. ... -
23
PyCBC
Learn how to use PyCBC to analyze gravitational-wave data
...Many of these tutorials will require you to make edits to config files as part of their exercises. At the moment this isn't easy to do on services like Google Colab. However, you can do them either on your local machine or by using services such as mybinder or sciserver which allow a full juypterhub experience with the ability to view and edit text files. Below we give links to the tutorials that should directly work in Google Colab, however. -
24
Boss Engine
8-bit Graphical API for Java
Boss Engine is a graphical API for writing low-resolution 8-bit color applications. It offers easy to use functions for handling graphics, basic i/o and more. Screen access is performed through virtual framebuffers that allow direct read/write access to indexed color screen data. API is coded entirely with native libraries. No third party libraries required. -
25
DeepLearning
Deep Learning (Flower Book) mathematical derivation
...It is edited by three world-renowned experts, Ian Goodfellow, Yoshua Bengio, and Aaron Courville. Includes linear algebra, probability theory, information theory, numerical optimization, and related content in machine learning. At the same time, it also introduces deep learning techniques used by practitioners in the industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling and practical methods, and investigates topics such as natural language processing, Applications in speech recognition, computer vision, online recommender systems, bioinformatics, and video games. ...
