BoxLang vs. Deeplearning4j vs. JavaScript vs. Visual Basic Comparison Chart

DL4J takes advantage of the latest distributed computing frameworks including Apache Spark and Hadoop to accelerate training. On multi-GPUs, it is equal to Caffe in performance. The libraries are completely open-source, Apache 2.0, and maintained by the developer community and Konduit team. Deeplearning4j is written in Java and is compatible with any JVM language, such as Scala, Clojure, or Kotlin. The underlying computations are written in C, C++, and Cuda. Keras will serve as the Python API. Eclipse Deeplearning4j is the first commercial-grade, open-source, distributed deep-learning library written for Java and Scala. Integrated with Hadoop and Apache Spark, DL4J brings AI to business environments for use on distributed GPUs and CPUs. There are a lot of parameters to adjust when you're training a deep-learning network. We've done our best to explain them, so that Deeplearning4j can serve as a DIY tool for Java, Scala, Clojure, and Kotlin programmers.

Visual Basic is an object-oriented programming language developed by Microsoft. Using Visual Basic makes it fast and easy to create type-safe .NET apps. Visual Basic focuses on supplying more of the features of the Visual Basic Runtime (microsoft.visualbasic.dll) to .NET Core and is the first version of Visual Basic focused on .NET Core. Many portions of the Visual Basic Runtime depend on WinForms and these will be added in a later version of Visual Basic. .NET is a free, open-source development platform for building many kinds of apps. With .NET, your code and project files look and feel the same no matter which type of app you're building. You have access to the same runtime, API, and language capabilities with each app. A Visual Basic program is built up from standard building blocks. A solution comprises one or more projects. A project in turn can contain one or more assemblies. Each assembly is compiled from one or more source files.