Over the past 12 months there has been an increase in the number of Machine Learning notebooks becoming available.
What is a Machine Learning notebook?
As the name implies it can be used to perform machine learning using one or more languages and allows you to organise your code, scripts and other details in one application.
The ML notebooks provide an interactive environment (sometimes browser based) that allows you to write, run, view results, share/collaborate code and results, visualise data, etc.
Some of these ML notebooks come with one language and others come with two or more languages, and have the ability to add other ML related languages. The most common languages are Spark, Phython and R.
Based on these languages ML notebooks are typically used in the big data world and on Hadoop.
Examples of Machine Learning notebooks include: (Starting with the more common ones)
- Apache Zeppelin
- Jupyter Notebook (formally known as IPython Notebook)
- Azure ML R Notebook
- Beaker Notebook
At Oracle Open World (2016), Oracle announced that they are currently working creating their own ML notebook and it is based on Apache Zeppelin. They seemed to indicate that a beta version might be available in 2017. Here are some photos from that presentation, but with all things that Oracle talk about you have to remember and take into account their Safe Habor.
I’m looking forward to getting my hands on this new product when it is available.