Solutions to labs and excercises from An Introduction to Statistical Learning, as Jupyter Notebooks.
-
Updated
Jul 20, 2024 - Jupyter Notebook
Solutions to labs and excercises from An Introduction to Statistical Learning, as Jupyter Notebooks.
[SOML'21] Reference material, tutorial notebooks and other resources for Summer of ML, organised by AIMLC IITD.
A Jupyter Notebook that implements in Python 3 the Eigenfaces algorithm for face recognition
Blank notebooks and solutions for the Mathematics for Machine Learning specialization by Imperial College of London on Coursera.
A small R notebook describing how plot common (aDNA) population genetics PCAs using R and the tidyverse.
Machine Learning exercises in Python (Jupyter notebooks)
Repo with my most popular kaggle notebooks. I've put a lot of effort into them back in the day, so they are highly curated and well documented.
This Notebook illustrate the calculation of Semantic Similarity using WordNet Embedding and Principal Component Analysis
In this repository, I have displayed some of the datasets I've worked upon.
This Repo contains Notebook for Anomaly Detection using Dimensionality Reduction techniques
Final year project experimenting with clustering and topological data analysis of scRNA-seq data using Python and R across two Jupyter notebooks
Principle Component Analysis in Python
In this notebook, I compared two famous clustering algorithm, the minibatchkmeans and the regular kmeans on cellular image dataset.
Jupiter notebook with EEG-data classification problem from the MNE library
Jupyter notebooks with notes, code, and exercises from Linear Algebra: Theory, Intuition, Code by Mike X Cohen (2021).
Principal Component Analysis Example Notebook.
Notebooks on PCA(Principal Component Analysis)
A notebook using many unsupervised learning techniques. PCA, K-means, Gaussian Mixtures. Clustering, dimensionality reduction, anomaly detection
Add a description, image, and links to the pca topic page so that developers can more easily learn about it.
To associate your repository with the pca topic, visit your repo's landing page and select "manage topics."