- Libraries and Tool, containing the Python libraries that are crucial for complex operations on large data sets
- Deep learning Frameworks, with Tensorflow / Keras originating from Google supporting neural networks for deep analysis of data
- Elastic AI and machine learning Infrastructure is underpinning the platform by a rich set of high performance components

Python
Python is the de-facto choice in the scientific and data science community. In these communities, multiple libraries are developed that support complex computational operations on large data sets. The syntax of Python is designed to be clear and readable, and is summarized in a Zen of Python. This Zen can be visualized by running “import this” in Python.

Jupyter

Anaconda

Python Libraries
- Numpy (Numerical Python) is the base class for numerical computing in Python (array handling, math functions, etcetera)
- Pandas (Panel Data and Python Data Analysis) is designed to work with tabular and heterogeneous data, and in a way the equivalent of Excel in Python.
- Matplotlib, not mentioned in the picture but most likely part of the AI stack delivers rich visualisation capabilities
- OpenCSV deals with CSV (comma-separated values) parser library for Java
- Pillow is the Python Imaging Library
- scikit-learn, contains Machine Learning in Python
Study Resources
- Pythonista editor on iPad
I started with a Dutch Python Book (Handboek Python or Python Apprentice) and worked on my iPad with the Pythonista editor - Python for Data Analysis (O’Reilly)
Good explanation of Numpy/Pandas/Matplotlib and a short intro on Python and Jupyter - Podcast https://talkpython.fm
My favorite weekly, hour-long podcast where usage of Python in different industries is discussed.
Oracle selected a set of Libraries and Tools for the Python Data Science and Machine Learning ecosystem for the Oracle AI Platform. This is a smart move since there is a very large scientific and data science and community that have been developing all sorts of libraries to support data crunching on large data sets. In the next blog, we will dive into the machine learning library scikit-learn.
This blog series was co-authored by Léon Smiers and Johan Louwers. Léon Smiers is an Oracle ACE and a thought leader on Oracle cloud within Capgemini. Johan Louwers is an Oracle ACE director and global chief architect for Oracle technology. Both can be contacted for more information about this, and other topics, via email; Leon.Smiers@capgemini.com and Johan.Louwers@capgemini.com