Start the Kernel.
Click on the "Create new notebooks" button .
Add the name of the notebook you want to create.
Save it at any time.
The code shown in the .gif image is a snippet for loading the iris dataset. For testing, enter the
code block below:
import smartpredict as spimport tensorflow as tfsp.api.dataset_load('iris_dataset')
Follow the wizard and insert the code as follows:
If you are already familiar with kindred notebooks such as Jupyter and the like, you will find the Notebooks an interesting alternative.
If you are yet to discover the SmartPredict Notebooks, you will soon see how you can customize your projects with them and will appreciate their handy functionalities.
The SmartPredict Library is a Python library for Data Science adopting the SmartPredict Studio workflow. It is built on top of many open source frameworks. The concept is to offer an easy way for people to engage into Data Science and Machine Learning with little effort.
You can export the content of a cell as a custom module's code. Both function and class types are supported.
You can save the content of a cell as a code snippet and reuse the code inside of it at any time for other projects.