Deep Netts8 articles
In this podcast, we are talking to some of the key people working on different IDEs, Integrated Development Environments.
Getting Started with Deep Learning in Java Using Deep Netts (Part 2)
For more complex deep learning challenges, more data, and need better performance, take a look at Deep Netts Professional Edition.
Getting Started with Deep Learning in Java Using Deep Netts
Learn how to make it easy to quickly start using deep learning and to integrate deep learning into existing Java applications.
Deep Learning in Java for Nuclear Physics using Deep Netts
We use the Deep Netts library to implement our neural networks to do track classification, using Multi-Layer Perceptron (MLP) Neural Network.
Visual Recognition for Chess with Deep Learning in Java on Android
Deep Netts is a lightweight Java-native library, easy to learn, and solves many technical challenges related to ML.
Deep Learning in Java for Drug Discovery
I see tremendous potential for Deep Netts in the drug discovery pipeline and I feel it is necessary to share Deep Netts existence with the scientific community.
As a Java developer, I have especially come to appreciate having a tool in my language that I could immediately use out of the box and not have to add on weeks, or even months, of training in order to become proficient in another language.
Open Source Tools as an Opportunity for SMEs to Use AI?
Time-traveling cyborgs and robots that are able to love. These interesting and romantic ideas emerged from the imagination of Hollywood film directors.
Nevertheless, many people are afraid of Artificial Intelligence (AI). This also can be seen in the economic world.
Small and medium-sized enterprises (SMEs), in particular, see AI as a threat to their own business. Surprisingly however, all different-sized companies are able to see the potential of AI when it comes to penetrating the national and global market.
Quick Start with Machine Learning in Java
So you’re a Java developer and you want to do some machine learning. Some of the questions that you might be wondering about are — what can machine learning do for me anyway, which library to use, which algorithm, and is there some common standard API?
Here is an example of Java code based on the VisRec API to build and use a classifier. Without any explanations, it should be clear to you what is happening.