updated readme with the eda images (#3)

- updated readme with the eda images (a534d17cb2795cbd274d0d265908ed6d670c9c6a)

README.md

@@ -69,26 +69,33 @@ Key features include:
 ## Exploratory Data Analysis
 
 ### Brand Distribution
+
+![Brand Distribution Treemap](https://raw.githubusercontent.com/calicartels/watch-market-gnn-code/main/images/2.png)
+
 The treemap visualization provides a hierarchical view of market presence:
 - Rolex dominates with the highest representation, reflecting its market leadership
-- Omega and Seiko follow as major players, indicating strong market presence
+- Omega and Seiko follow as major players, indicating a strong market presence
 - Distribution reveals clear tiers in the luxury watch market
 - Brand representation correlates with market positioning and availability
 
-[Treemap Image]
 
 ### Feature Correlations
+
+![Feature Correlation Matrix](https://raw.githubusercontent.com/calicartels/watch-market-gnn-code/main/images/3.png)
+
 The correlation matrix reveals important market dynamics:
 - **Size vs. Year**: Positive correlation indicating a trend toward larger case sizes in modern watches
 - **Price vs. Size**: Moderate correlation showing larger watches generally command higher prices
 - **Price vs. Year**: Notably low correlation, demonstrating that vintage watches maintain value
 - Each feature contributes unique information, validated by the lack of strong correlations across all variables
 
-[Correlation Matrix Image]
 
 ### Market Structure Visualizations
 
 #### UMAP Analysis
+
+![UMAP Visualization](https://raw.githubusercontent.com/calicartels/watch-market-gnn-code/main/images/4.png)
+
 The UMAP visualization unveils complex market positioning dynamics:
 - Rolex maintains a dominant central position around coordinates (0, -5), showing unparalleled brand cohesion
 - Omega and Breitling cluster in the left segment, indicating strategic market alignment
@@ -96,9 +103,11 @@ The UMAP visualization unveils complex market positioning dynamics:
 - Premium timepieces (yellower/greener hues) show tighter clustering, suggesting standardized luxury attributes
 - Smaller, specialized clusters indicate distinct horological collections and style categories
 
-[UMAP Image]
 
 #### t-SNE Visualization
+
+![t-SNE Analysis](https://raw.githubusercontent.com/calicartels/watch-market-gnn-code/main/images/5.png)
+
 T-SNE analysis reveals clear market stratification with logarithmic pricing from $50 to $3.2M:
 - **Entry-Level Segment ($50-$4,000)**
  - Anchored by Seiko in the left segment
@@ -109,12 +118,13 @@ T-SNE analysis reveals clear market stratification with logarithmic pricing from
  - Cartier demonstrates strategic positioning between luxury and mid-range
 - **Ultra-Luxury Segment ($35,000-$3.2M)**
  - Dominated by Patek Philippe and Audemars Piguet
- - Clear separation in right segment
+ - Clear separation in the right segment
  - Strong brand clustering indicating market alignment
 
-[t-SNE Image]
-
 #### PCA Analysis
+
+![PCA Visualization](https://raw.githubusercontent.com/calicartels/watch-market-gnn-code/main/images/6.png)
+
 Principal Component Analysis provides robust market insights with 56.6% total explained variance:
 - **First Principal Component (31.3%)**
  - Predominantly captures price dynamics
@@ -125,28 +135,33 @@ Principal Component Analysis provides robust market insights with 56.6% total ex
 - **Brand Trajectory**
  - Natural progression from Seiko through Longines, Breitling, and Omega
  - Culminates in Rolex and Patek Philippe
- - Diagonal trend line serves as market positioning indicator
+ - Diagonal trend line serves as a market positioning indicator
 - **Market Implications**
  - Successful brands occupy optimal positions along both dimensions
  - Clear differentiation between adjacent competitors
  - Evidence of strategic market positioning
 
-[PCA Image]
 
 #### Network Visualizations
 
+
 **Force-Directed Graph**
+
+![Force-Directed Graph](https://raw.githubusercontent.com/calicartels/watch-market-gnn-code/main/images/7.png)
+
 The force-directed layout reveals natural market clustering:
 - Richard Mille's peripheral positioning highlights ultra-luxury strategy
 - Dense central clustering shows mainstream luxury brand interconnectivity
 - Edge patterns reveal shared market characteristics
 - Node proximity indicates competitive positioning
 
-[Force-Directed Graph Image]
 
 **Starburst Visualization**
+
+![Starburst Graph](https://raw.githubusercontent.com/calicartels/watch-market-gnn-code/main/images/8.png)
+
 Radial architecture provides a hierarchical market perspective:
-- Central node represents overall market
+- Central node represents the overall market
 - Green nodes show brand territories with strategic spacing
 - Blue peripheral nodes indicate individual timepieces
 - Node density reveals:
@@ -155,8 +170,6 @@ Radial architecture provides a hierarchical market perspective:
  - Segment diversification
 - Balanced spacing between brand nodes indicates market segmentation
 
-[Starburst Graph Image]
-
 
 ## Ethics and Limitations
 
@@ -334,4 +347,4 @@ def get_watch_features(watch_id):
 ## Note
 - The dataset is optimized for PyTorch Geometric operations
 - Recommended to use GPU for large-scale operations
-- Consider batch processing for memory efficiency
+- Consider batch processing for memory efficiency