This week subject is a classic in distributed computing: Paxos which is so popular that it almost became a synonym of consensus.
First let’s start by examining the problem faced by distributed system and why we need a consensus algorithm.
Continue reading “Basic Paxos”
Following my previous post on ND4J I think it’s time for a proper introduction to deepLearning4J (a.k.a. DL4J).
In this post I’ll try to do something similar to the tensorflow introduction. That is installing DL4J, get our hands on it and then build a very basic neural network.
Continue reading “DeepLearning4J introduction”
I have spent years programming in Java and one thing (among others) that I found frustrating is the lack of mathematical libraries (not to say Machine learning framework) on the JVM.
In fact if you’re a little interested in machine learning you’ll notice that all the cool stuffs are written in C++ (for performance reasons) and most often provide a Python wrapper (because who wants to program in C++ anyway).
Continue reading “Nd4j – Numpy for the JVM”
The idea from this blog post came after finishing the lab on TF-IDF of the edx Spark specialisation courses.
In this course the labs follow a step-by-step approach where you need to write some lines of code at every step. The lab is very detailed and easy to follow. However I found that focusing on a single step at a time I was missing the big picture of what’s happening overall.
Continue reading “TF-IDF”