Deeplearning4j vs. MLlib vs. Ping-API vs. SQLite Data Access Components 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.

Use our generator to create a test script in JavaScript or CoffeeScript. Write script to set the request parameters and validate the response. Ping-API will run your test script on global servers in U.S., Japan, Germany and Singapore. Schedule testing to inspect your APIs. We will send the failure test information to you with email, Slack and HipChat. Ping-API allows you to write test script in JavaScript and CoffeeScript to test your APIs. Write script to set request url parameters, headers and body. And write script to validate response headers and body. Script generator. Don't worry about programming. Just set parameter of your API, the generator will give you test script. It is easy! The use case for web developers. Give me a notification when my web is down or the response is unexpected. Ping-API will schedule your tests in every minutes or hours. If the test is failure, we will send the notification to you.