Unlock the Power of Machine Learning in Excel with Python 🚀

Learn to combine Excel’s hands-on nature with Python’s machine learning capabilities to get the best of both worlds with Python in Excel.

In this demo, you’ll learn how to fit, interpret, and visualize a K-Means Clustering model in an Excel workbook with less than 15 lines of Python code.

Along the way, you’ll use Python in Excel to:
✔️ View column distributions using pair plots
✔️ Scale data using normalization
✔️ Find the right number of clusters using inertia plots
✔️ Fit a K-Means clustering model
✔️ Interpret the cluster centers
✔️ Visualize the clusters to share your insights
…all in less than 20 minutes!


🔗 Helpful links:

👉 Downloadable project file: https://drive.google.com/drive/folders/1WGDRIzcq0nqqErNOmM4DBjoMl-G2hvCb?usp=sharing

👉 Full Unsupervised Learning course:
Maven Analytics: https://bit.ly/4eLsOX6
Udemy: https://bit.ly/3Y4y1lT

👉 10-Week Immersive Programs: https://bit.ly/3AceEzc

👉 Follow us on LinkedIn:
Enrique: https://www.linkedin.com/in/enrique-ruiz-tapia/
Maven Analytics: https://www.linkedin.com/company/maven-analytics


⏱️ Timestamps:
00:00 - Intro
00:15 - Excel + Python
00:45 - Marvel Movie Dataset
00:56 - Step 1: Start with a question
01:11 - Step 2: Select the right method
01:34 - Step 3: Select the right features
03:24 - Step 4: Scale the data
05:54 - Step 5: Find the right number of clusters
09:13 - Step 6: Fit the model
10:11 - Step 7: Interpret the cluster centers
12:33 - Step 8: Share your insights
15:35 - Resources and next steps



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