Exploration of RayTracing using pre-existing graphical library mlx
https://education.siggraph.org/static/HyperGraph/raytrace/rayplane_intersection.htm
https://kylehalladay.com/blog/tutorial/math/2013/12/24/Ray-Sphere-Intersection.html
- Quaternion rotation
- Optics
- Distance computation in Euclidean space
- Distance calculations for creating new features.
- Normalization and scaling of data.
- K-means Clustering: Uses Euclidean distances for grouping.
- K-nearest Neighbors (KNN): Relies on distance measurements.
- Support Vector Machines (SVM): Uses geometry and distances for decision boundaries.
- Principal Component Analysis (PCA): Utilizes geometric relationships.
- t-SNE and UMAP: Uses distances for data visualization in lower dimensions.
- Computer Vision: Object detection, 3D reconstruction.
- Natural Language Processing (NLP): Similarity measurements in embedding spaces.
- K-means++ initialization: Improved cluster initialization for faster convergence.
π§ Practical Steps:
- Implement Algorithms: Practice implementing distance-based algorithms like KNN and K-means.
- Data Visualization: Use graphical tools to visualize data in different dimensions.
- Competitions: Participate in Kaggle competitions to apply these concepts on real datasets.