chore: import upstream snapshot with attribution

2026-07-13 13:38:23 +08:00
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+# Image Gallery
+
+This previous image gallery have been removed to avoid duplication and to keep the file size of this GitHub repository slim, since the high-res version of these images are now embedded in the Jupyter notebooks themselves in the [code](../../code/) directory. 
+
+Below are the links to the respective images by chapter:
+
+- [ch01](../../code/ch01/images) - Machine Learning - Giving Computers the Ability to Learn from Data
+- [ch02](../../code/ch02/images) - Training Machine Learning Algorithms for Classification
+- [ch03](../../code/ch03/images) - A Tour of Machine Learning Classifiers Using Scikit-Learn
+- [ch04](../../code/ch04/images) - Building Good Training Sets - Data Pre-Processing
+- [ch05](../../code/ch05/images) - Compressing Data via Dimensionality Reduction
+- [ch06](../../code/ch06/images) - Learning Best Practices for Model Evaluation and Hyperparameter Optimization
+- [ch07](../../code/ch07/images) - Combining Different Models for Ensemble Learning
+- [ch08](../../code/ch08/images) - Applying Machine Learning to Sentiment Analysis
+- [ch09](../../code/ch09/images) - Embedding a Machine Learning Model into a Web Application
+- [ch10](../../code/ch10/images) - Predicting Continuous Target Variables with Regression Analysis
+- [ch11](../../code/ch11/images) - Working with Unlabeled Data – Clustering Analysis
+- [ch12](../../code/ch12/images) - Training Artificial Neural Networks for Image Recognition
+- [ch13](../../code/ch13/images) - Parallelizing Neural Network Training via Theano