Search Results for "java machine learning library"
Sort By:
Showing 14 open source projects for "java machine learning library"
View related business solutions-
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.
-
Keep company data safe with Chrome EnterpriseMake AI work your way with Chrome Enterprise. Block unapproved sites and set custom data controls that align with your company's policies.
-
1
TensorFlow.js
TensorFlow.js is a library for machine learning in JavaScript
TensorFlow.js is a library for machine learning in JavaScript. Develop ML models in JavaScript, and use ML directly in the browser or in Node.js. Use off-the-shelf JavaScript models or convert Python TensorFlow models to run in the browser or under Node.js. Retrain pre-existing ML models using your own data. Build and train models directly in JavaScript using flexible and intuitive APIs. -
2
SageMaker Training Toolkit
Train machine learning models within Docker containers
Train machine learning models within a Docker container using Amazon SageMaker. Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows. You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. To train a model, you can include your training script and dependencies in a Docker container that runs your training code. -
3
TensorFlow Model Garden
Models and examples built with TensorFlow
The TensorFlow Model Garden is a repository with a number of different implementations of state-of-the-art (SOTA) models and modeling solutions for TensorFlow users. We aim to demonstrate the best practices for modeling so that TensorFlow users can take full advantage of TensorFlow for their research and product development. To improve the transparency and reproducibility of our models, training logs on TensorBoard.dev are also provided for models to the extent possible though not all models... -
4
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. -
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
-
5
Edward
A probabilistic programming language in TensorFlow
...Edward fuses three fields, Bayesian statistics and machine learning, deep learning, and probabilistic programming. Edward is built on TensorFlow. It enables features such as computational graphs, distributed training, CPU/GPU integration, automatic differentiation, and visualization with TensorBoard. Expectation-Maximization, pseudo-marginal and ABC methods, and message passing algorithms. -
6
SynthePG
Live Music Compositor learning base on TPG
This android app is producing music and partition sheets in real time. Furthermore, the AI module can be activated and be trained to learn you prefered style and play it. You can also team play your music with the interconnect mode. Finally, move your phone like a 'chef d'orchestre' and see how it changes the music... -
7
GUAJE FUZZY
Free software for generating understandable and accurate fuzzy systems
GUAJE stands for Generating Understandable and Accurate fuzzy models in a Java Environment. Thus, it is a free software tool (licensed under GPL-v3) with the aim of supporting the design of interpretable and accurate fuzzy systems by means of combining several preexisting open source tools, taking profit from the main advantages of all of them. It is a user-friendly portable tool designed and developed in order to make easier knowledge extraction and representation for fuzzy systems, paying... -
8
JUMLStateMachine
Java library implementing a state machine by the UML standard.
JUMLStateMachine is a Java library implementing a state machine by the UML standard. The purpose for the library is to be easily usable for small state machines, yet extendable and scalable for larger and more complex ones. -
9
MOCASEngine is a java UML state machine engine library for executing embedded UML state machine models. MOCASEngine works with Eclipse EMF. It has a full support of composite/orthogonal states, completion transitions, guard, hierarchy of signals, ...
-
Field Service Management Software | BlueFolderTrack all your service data in one easy-to-use system, enabling your team to move faster and generate more revenue for your bottom line.
-
10
Simple implementation of finite state machine concepts. The project contain ease-to-use library and modeling graphical tool. Project define simple identical API for Finite State Machines for both language bindings (C# and Java).
-
11
This project has been moved to the Tungsten project, which contains a number of Tungsten technologies together. Please visit at http://sourceforge.net/projects/tungsten. This project will not be further maintained.
-
12
Many design artifacts can be directly executed. UML state processes can be executed by a state machine; UML sequence diagrams can be executed directly. ExecDesign will be a suite of Java tools which can be used to document and execute UML designs.
-
13
jStates is a java library for easy state machine design and implementation.It uses XML to define states and state transitions. jStates is aimed at easy integration with desktop J2SE applications, Struts, Commons Validator, Web and other J2EE technologies
-
14
JSpasm is a pure Java package for developing event-driven, state-based software applications and packages. This small-footprint package will handle multiple models and large numbers of entities in parallel, and includes features to support SMP operation.
- Previous
- You're on page 1
- Next
