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...Built on top of TensorFlow.js, the ml5.js library provides access to machine learning algorithms and models in the browser with a concise, approachable API. Comfortable with concepts like Tensors, Layers, Optimizers and Loss Functions (or willing to get comfortable with them)? TensorFlow.js provides flexible building blocks for neural network programming in JavaScript.

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. A container provides an effectively isolated environment, ensuring a consistent runtime and...

...Link: https://graphviz.org/ Report an error or suggest an improvement: https://bitbucket.org/rrrfer-admin/uchebnaia-sreda-proektirovaniia/issues?status=new&status=open Ask a question and get advice: https://github.com/topics/forum About PlantUML: https://plantuml.com/

...Normal code generator flow: Template → Source Code Jmr development automation flow: Template/Model/Action → Task → Source Code/Test Case/Document Template: Support Java Script(<%%> JSP-like) and Jmr Tag(set/get/for...) Model: Database Model(like Table/View), Java POJO Model, Xml File Model and includes Transform/Mapping/Convert Tool Action: A Java Class can set Java variables to template. Support any kind of project Maven, Gradle, Web, Java, Android, PHP, Python etc. Support any kind of framework spring/springMVC, hibernate, ibatis/mybatis, struts/struts2, JPA etc. ...

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/. ...

...Its goal is to make state machine declaration and use easy enough that it can be integrated into your projects painlessly. Have a look atp the wiki where you will find a tutorial, samples, and a cheatsheet to get accustomed with instantFSM. The only instantFSM header file is downloadable from the files section or you can check it out from the git repository.

Multi-categorization Recommendation Adjusting (MRA) is to optimize the results of recommendation based on traditional(basic) recommendation models, through introducing objective category information and taking use of the feature that users always get the habits of preferring certain categories. Besides this, there are two advantages of this improved model: 1) it can be easily applied to any kind of existing recommendation models. And 2) a controller is set in this improved model to provide controllable adjustment range, which thereby makes it possible to provide optional modes of recommendation aiming different kinds of users.

Jact is a tool to provide severval ways of configurating the Asterisk PBX. It's base upon UML2 models of the configuration files. The goal is to get a functional description of all configuration elements around the Asterisk.

redVoodo uses Vaadin + OSGI and provides informations, HowTo's and also a framework to design und develop dynamic and modular business web applications. You'll get best practices HowTo use Vaadin and OSGI together.

It's an infrastructure helps engineers to develop enterprise software solutions in Microsoft .NET easily and productively which consists of an extendable and maintainable web system architecture with a suite of generic business model, APIs and servi

Java objects that share parts of immutable graphs. Reused subgraphs have directly or indirectly recursive Elements. Selected components get replaced by new counterparts in Context of Mirrors - translation tables. Deep copies are not involved.

Multiform allows creation of Web Applications by defining their processes and business objects in a declarative XML-based language. It's made of a Javascript framework and an XSL compiler to get the application skeleton from the definitions.

The DesignPatternDemo contains saveral design patterns' demo code,maybe you can get some help from it when your study design pattern.