JupyterLab Sample Notebooks
Tracking experimentation in ML flow via Notebooks
The notebook trains a machine learning model on the diabetes dataset while using MLflow to track experiments and manage the model lifecycle through registration and logging. Here’s a step-by-step explanation of what it does:
Creating a simple propensity model in a Notebook
Below is an example of creating a simple propensity model using Python in a JupyterLab/Syntasa Notebook. In this example, we’ll use a logistic regression model from scikit-learn to estimate an event's probability (i.e., the propensity) (for example, a conversion or treatment) based on a couple of…
Getting Started with SparkSQL
This tutorial introduces Spark SQL programming within a JupyterLab environment (assuming Python is used). It demonstrates how to:
Reading & Writing a CSV File
This article demonstrates how to use PySpark in a Jupyter Notebook to read data from Amazon S3, perform transformations (filtering and joining), and write the results back to S3. This workflow is commonly used for quick data exploration, validation, or prototyping before integrating the logic into…
Importing Libraries in JupyterLab: A Beginner's Guide
JupyterLab, a powerful interactive environment for Python, allows you to seamlessly work with various libraries to enhance your data analysis, visualization, and machine learning projects. This guide will equip you with the essential knowledge on how to import libraries and get started with using…
Getting Started with TensorFlow
This code provides a basic example of training a binary classification model with TensorFlow in JupyterLab. You can adapt this structure for more complex tasks by modifying the model architecture, data preparation steps, and training parameters.
Credentials Store in Notebooks
Introduced in Syntasa 6.3 , the credentials store enables you to create, save, and share credentials as an object so that other users can use them without the details being revealed. This sample demonstrates how to create and utilize credentials within a notebook.