An Oracle Machine Learning notebook supports multiple languages. Each paragraph is associated with a specific interpreter. To run Python commands in a notebook, you must first connect to the Python interpreter. To use OML4Py, you must import the oml module.

1. Open the Py Note notebook and click the interpreter bindings icon. View the available interpreter bindings.
2. To connect to the Python interpreter, type %python
   You are now ready to run Python scripts in your notebook.
3. To use OML4Py module, you must import the oml module. Type the following Python command to import the oml module, and the click run icon. Alternatively, you can press Shift+Enter keys to run the notebook.
   import oml
4. To verify if the oml module is connected to the Database, type:
   oml.isconnected()
   
   Description of the illustration connect_python.eps
   Once your notebook is connected, the command returns TRUE. The notebook is now connected to the Python interpreter, and you are ready to run python commands in your notebook.

Example to demonstrate the use of the Python modules - matplotlib and numpy , and use random data to plot two histograms.

5. Type the following commands to import the modules:

   %python
   import matplotlib.pyplot as plt
   import numpy as np

   • Matplotlib - Python module to render graphs
   • Numpy - Python module for computations
6. Type the following commands to compute and render the data in two histograms.

   
   list1 = np.random.rand(10)*2.1
   list2 = np.random.rand(10)*3.0
   
   plt.subplot(1,2,1) # 1 line, 2 rows, index nr 1 (first position in the subplot)
   plt.hist(list1)
   plt.subplot(1, 2, 2) # 1 line, 2 rows, index nr 2 (second position in the subplot)
   plt.hist(list2)
   plt.show()

   In this example, the commands import two Python module to compute and render the data in two histograms list1 and list2.
7. Click Run.
   
   

   
   Description of the illustration python-script.eps

   
   
   The output section of the paragraph which contains a charting component displays the results in two histograms - list1 and list2, as shown in the screenshot.

• About Oracle Machine Learning for Python
  Oracle Machine Learning for Python (OML4Py) is a component of Oracle Autonomous AI Database, which includes Oracle Autonomous AI Lakehouse (ADW), Oracle Autonomous AI Transaction Processing (ATP), and Oracle Autonomous AI JSON Database (AJD). By using Oracle Machine Learning UI notebooks, you can run Python functions on data for data exploration and preparation while leveraging Oracle AI Database as a high-performance computing environment. Oracle Machine Learning User Interface (UI) is available through Autonomous AI Lakehouse (ADW) , Autonomous AI Transaction Processing (ATP) and Autonomous AI JSON Database (AJD) services.