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This blog post is about the two machine-learning frameworks Smile and DeepLearning4j. I am presenting my feedback and some hints useful for any Java developers interested in machine learning.
Introduction and disclaimer
This blog post is based on my own experience with Machine learning frameworks and java coding. I am not the most efficient or skilled data scientist or expert in the ML domain though I have been using it for some research use-cases in the past and for a real in-production service this year.
I have been using machine-learning (and deep-learning) for the following use-cases (classification problems):
- How to identify code and bugs based on a certain type of code ie initialization code, exception code, IO code etc
- How to identify a security leak into a code? the sink, the source, the incriminated leak? especially faults by injection.
NLP Problem / how to identify newspaper titles or articles that may become viral?
Experiments
I began my experiments with NLP with the following frameworks and they were great :
- Knime: https://www.knime.com/
- Weka: https://www.cs.waikato.ac.nz/ml/weka/
- Tensorflow using Google Colaboratory. https://colab.research.google.com/
