List of Kaggle notebooks

Notebooks on PCA (Principal Component Analysis).

Mathematics for Machine Learning Notebooks and files

Various Template Notebooks for Deploying ML models with Amazon Sagemaker

This Python notebook demonstrates the application of Support Vector Machines (SVM) for classification tasks on the MNIST dataset. The notebook covers data preprocessing, hyperparameter tuning, and dimensionality reduction using PCA.

A.I. and Machine Learning notebooks: Using Supervised Learning, Unsupervised Learning, Re-enforcement Learning to solve Classification, Clustering and Regression problems

A linear algebra and machine learning in Scala hands-on based on a Databricks community cloud notebook using Breeze and Spark MLlib.

This Jupyter Notebook demonstrates the implementation of a K-Nearest Neighbors (KNN) algorithm using the concept of nearest neighbors without using direct classifiers. It also includes exploratory data analysis (EDA) and comparison of three classifiers.

Jupyter notebook using machine learning techniques to explore the complex drivers of modern slavery. Models from a research paper are replicated and evaluated . Actions also include filling missing data, training regression models, and analyzing feature importance.

The purpose of this project is to promote understanding -- my own and others' -- of fundamental data science and machine learning concepts and tools. It currently consists of one notebook that classifies fruit types based on weight, volume, and image data.

Study Notes on machine learning, data analysis, algorithms and best practices using Python and Jupyter Notebook.

Principal Component Analysis Example Notebook.

Repository for the Wine K-Means Clustering Kaggle notebook.

Introduction to Principal Component Analysis with scikit-learn

Jupyter notebooks implementing Machine Learning algorithms in Scikit-learn and Python

This repository is a series of notebooks that show analysis and modeling of the Breast Cancer data from Kaggle.

This repository contains a highly detailed notebook that serves as an assignment for the Data Analysis course at the Higher School of Computer Science ESI. The notebook covers the topic of PCA (Principal Component Analysis), providing thorough explanations and examples.

This repository contains a Jupyter Notebook that implements PCA (Principal Component Analysis) from scratch for facial recognition. It demonstrates the steps involved in PCA, including eigenface computation and accuracy comparisons for different components.

Face-Recognition Notebook & Demo using principal component analysis.

Notebook to Perform Market Segmentation using K-means clustering, PCA, and Auto-encoders.