How to get started with Java machine learning

What is the best tool for starting Java machine learning?

The problem has been around for some time now, but almost everyone has been talking about AI and machine learning these days. This is no longer a secret that is reserved for scientists and researchers, but almost every emerging technology.

In the following chapters, we will do a quick overview of the main framework of machine learning in Java and demonstrate how easy it is to learn Java machine learning without having to start a new one or create an algorithm from scratch.

Artificial intelligence of human beingsAi has been a broad and cool field for some time, but it's always felt a little hard to touch, especially for scientists. If you want to create an AI system, you must implement your own core algorithms and train them to recognize patterns, understand images, and work with natural languages.

Recent developments in this area have made it easier for non-researchers to reach. You can now easily reach the relevant algorithms and tools. You don't need to know what you're doing, but it's easy to improve your application's machine learning skills.

let the machine run .For a simpler elaboration, we decided to select 3 projects to help you get started:

1.deeplearning4j (dl4j) – Open source, distributed, JVM Business Deep learning Lib Library

2. BID Data project– can run fast, large-scale collection of machine learning and data mining patterns

3. neuroph– object-oriented neural network

By the way, we recently released another interesting open source GitHub library that attracts our attention. Download.

dl4j– Deep Learning

DL4J is a tool that can help you configure a multilayer neural network. It provides deep learning for the JVM and accompanies rapid prototyping and mass customization, while focusing on more conventions than configuration.

This tool is designed to help those who already have the theory of creating and using neural networks, but do not want to implement the algorithm themselves. You can solve specific problems and customize neural network properties on massive amounts of data. DL4J is written in the Java language and can be compatible with any JVM language such as Clojure, Scala, Kotlin, and can be integrated with Hadoop and spark.

Possible use cases include evaluation or referral systems such as (Crm,adtech, churn prevention), predictive analytics and even fraud detection. If you are looking for a real case, you can download Rapidminer. This is an open source platform that uses dl4j to simplify the predictive analysis process for users.

Creating a new neural network is as easy as creating a new project.

BID Data Project (Big Data projects)

Big data projects are created by people who need to process large amounts of data and are sensitive to performance. The UC Berkeley Project is a collection of hardware, software, and design patterns that enable the use of fast, large-scale data mining.

The first library is Bidmach, which has a record of common machine learning problems on a single node or cluster. You can use this library to manage data sources, optimize and distribute data on the CPU or GPU.

Bidmach includes many popular machine learning algorithms, and their team is working on developing distributed neural networks, graphics algorithms, and other models

The other two libraries are Bidmat and Bidparse respectively. Bidmat is a library of fast mathematical matrices focused on data mining, and Bidparse is a natural language resolution for GPU acceleration. Other class libraries for big data projects also include visualization tools that can support class libraries that are running in spark or even on Android. The Bidmach benchmark continues to show better results than other solutions. Even its operation on a single machine is comparable to that of other scenarios on a large cluster. A complete list of benchmarks can be found here.

Neuroph

Neuroph is a lightweight Java framework used to develop commonly used neural network architectures. The framework provides a Java library and a GUI tool (called easyneurons) that you can use to create and train your own neural networks in a Java project.

Neuroph contains an open source Java class Library and a small number of base classes that correspond to basic neural network concepts. Neuroph is a great stepping stone for people who are just beginning to use neural networks, or want to know how they work. You can try Neuroph's online demo to see how it works. Tip: The interface looks old and outdated, but you can use it to create wonderful things. It also won the 2013 Duke's Choice Award.

Network view

What about other projects?

In case the above three items are not what you need, you want to look for something different for your project, it doesn't matter. If you search for "machine learning" on GitHub, you'll have 1506 Java resources to find the right tool.

For example, an interesting project in Airbnb is Aerosolve, a machine learning library designed to be human-friendly. Getting started with a new technology is a hassle, and if you're looking for some help, make sure you've downloaded the TAKIPI Error Analysis tool.

The final thought

Every few years there will be some new sounds about AI. This time, it is accompanied by the reinforcement of machine learning, data mining, neural networks and so on, which we all support. The fact that these libraries are open source means that the information and capabilities are up for grabs, and all you do is think about what you can do with that ability.

Http://www.importnew.com/22663.html

How to get started with Java machine learning