Скачать или смотреть K-Means Clustering Python Tutorial using PCA, Llama LLM, Streamlit & Power BI for Deployment

In this video, we walk through a complete unsupervised machine learning project using KMeans clustering on heart disease data from Kaggle. This tutorial covers every step, from data preparation to deployment and visualization, making it perfect for anyone looking to learn and apply ML in real-world scenarios.

🔗 *Tools Used:* Python, Jupyter Notebooks, Streamlit, Power BI, Groq API (Llama), KMeans, PCA, Visual Studio Code, Inertia, Dentogram

What we cover:
1️⃣ Data Preparation:
• Loaded the heart disease dataset from Kaggle into Jupyter Notebooks.
• Cleaned, preprocessed, scaled, and visualized the data.
2️⃣ Clustering Process:
• Used the Elbow Method and Inertia to find the best number of clusters.
• Explored data further with a Dendrogram.
• Ran the KMeans algorithm to group the data.
3️⃣ Dimensionality Reduction:
• Applied PCA to reduce dimensions and visualize the clusters in 2D.
4️⃣ LLM Integration:
• Used Groq's Llama LLM to summarize the cluster characteristics using natural language.
5️⃣ Deployment:
• Stored the KMeans model, scaler, and analysis with pickle for reusability.
• Built an interactive Streamlit app where users can input their data to predict their cluster and see cluster characteristics generated by Llama.
• Included scatter plot visualizations of the first two PCA components in the app.
6️⃣ Bonus Visualization:
• Created a Power BI dashboard to showcase the analysis with clean and intuitive visuals.

Why Watch?
This video is a practical guide for anyone looking to build and deploy machine learning projects. Whether you're a beginner or experienced, you'll find value in the hands-on approach, combining Python, Streamlit, Llama LLM, and Power BI.
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🔗 Chapters:
00:00 – Intro
02:26 – Loading the Data
03:07 – Data Preprocessing
06:42 – Elbow & Inertia
09:39 – Running Kmeans
10:17 – Principal Components Analysis (PCA)
12:35 – Summarizing our Results
14:13 – LLAMA LLM Groq API
17: Exporting our Model & Analysis

Python Part 1:    • K-Means Clustering Python Tutorial using P...  
Streamlit Part 2:    • How to deploy a Kmeans Clustering ML model...  
Power BI Part 3:    • How to Create a Power BI Dashboard to shar...  

Github Link: https://github.com/Pitsillides91/pyth...
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