ermaconomist / ml-handson-datasphere

🚀 ML-/ Datasphere Hands-On Workshop: Unleashing the Power of Machine Learning with SAP HANA & Python 🐍

🌟 Description

Welcome to this immersive ML-/ Datasphere Hands-On Workshop, brought to you by your Swiss SAP Team & Global Center of Excellence! Whether you're joining us on-site or virtually, this repository is your treasure trove of knowledge. Dive deep into the intricacies of Machine Learning as we guide you through a Python Client for SAP HANA and explore the limitless possibilities with SAP Datasphere.

🛠️ Requirements

Before you embark on this enlightening journey, there are a few prerequisites to take care of. Don't worry, we've got you covered with a comprehensive guide, which you can find below.

📚 Material Organization

The workshop material is organized into a sequence of interactive exercises, each encapsulated in its own Jupyter Notebook respective Markdown file. Navigate through these notebooks as you would through a storybook, each chapter revealing new facets of Machine Learning and SAP technologies.

🧭 How to Follow the Exercises

Finished an exercise ahead of time? Fantastic! But hold your horses 🐎— instead of rushing to the next exercise, take a moment to delve deeper into what you've just learned. Experiment, explore, and perhaps even discover something new! This way, we all stay in sync and enrich our learning experience through collective reflection and discussion.

Set Up:

1. Setup your Github Account
2. Fork this repository
3. Activate your Codespace

📋 Exercise Overview

Before you jump into the exercises, make sure you've successfully completed all the setup steps.

The exercises

Datasphere Exercises:

4. Datasphere Tutorial

Machine Learning Exercises:

5. Configure your credentials.json, defined in the prior step

These are the jupyter notebooks, that will be executed in your own codespace, created under 3.
Clicking these links, will display the static version.

6. Data Exploration and preparation
7. Create a first forecast with Hana ML
8. Create a forecast with hyperparameter tuning

Never used a Jupyter Notebook? Click here for more Infos!

How To run a Jupyter Notebook Cell by Cell:

License

Copyright (c) 2023 SAP SE or an SAP affiliate company. All rights reserved. This project is licensed under the Apache Software License, version 2.0 except as noted otherwise in the LICENSE file.