Use transfer learning for image classification followed by clustering to create/identify clusters in images
-
Updated
Jul 25, 2019 - Jupyter Notebook
Use transfer learning for image classification followed by clustering to create/identify clusters in images
It contains Google colab notebooks which I have created based on Data analysis and different Machine learning Techniques.
Notebook version implementation of unsupervised learning techniques. Analysis and Visualization.
NBA players clustering and Points prediction
Machine learning course at IDC. Implemented several amount of ML algorithms in Python using Jupyter notebooks
A Jupyter notebook that run PCA and KMeans on population demographic data.
Notebook to enrich clustering going a little bit beyond Sklearn
If you liked my analysis, pls upvote my notebook!
This project used a Kmeans after PCA model to segment retail customers to optimize marketing efforts. When the model repeatedly returned a single cluster, the model was used to prove the customers' homogenous characteristics. Influenced the bank's marketing strategies and initiatives. Developed in Jupyter Notebook with Python for FNB.
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning
This repository contains notebooks based on kaggle challenge of customers segmentation using ML.
The "Random Swap" algorithm with a random dataset, visuals and example notebooks
Notebooks for Global AI Hub ML course in Aug 2022
A Jupyter Notebook with a Clustering and PCA Analysis of a Spotify songs dataset.
Jupyter Notebook: documentation of the implementation of the ToMATo algorithm to the GUDHI library (Topological Data Analysis), using real datasets.
This repository contains a customer segmentation project implemented in a Jupyter Notebook using Python. Customer segmentation is a crucial strategy for businesses aiming to understand their customer base better, enabling targeted marketing strategies and personalized customer experiences.
This project contains a Jupyter Notebook project focused on analyzing customer data. The project involves Exploratory Data Analysis (EDA), data preprocessing, and the implementation of clustering algorithms to derive insights from the data.
- Notebook making penguin cluster using KMeans algorithm.
This repository houses a diverse collection of projects developed using Jupyter Notebooks, focusing on testing various machine learning pipelines, neural network models, and statistical machine learning approaches. Through exploration of different datasets, the projects delve into predictive modeling, classification tasks, and in-depth analyses.
Add a description, image, and links to the clustering-algorithm topic page so that developers can more easily learn about it.
To associate your repository with the clustering-algorithm topic, visit your repo's landing page and select "manage topics."