An approach to document exploration using Machine Learning. Let's cluster similar research articles together to make it easier for health professionals and researchers to find relevant research articles.

A node application that suggests the safest path between two places in Delhi by applying unsupervised machine learning, kmeans-clustering on crime data of the past.

WITH THE FIFA20 DATASET WE NEED TO CLUSTER THE PLAYER BY THEIR SKILL INTO CERTAIN GROUP

Digging for Data ⛏️

This project analyses data from missing females in the USA. I have performed Exploratory Data Analysis(EDA), KMeans, and Spatial clustering.

Identifying customer segments for mail-orders company and performing a comparison with the general population

Recommending movies using k-means clustering and cosine similarity

KMeans Clustering using Spark on Uber's ride share data - Case Study (Big Data Analytics @uber)

Explore my Document Clustering and Theme Extraction project, offering effective tools for organizing and extracting valuable insights from extensive text datasets. The objective is to provide a systematic approach to comprehend and organize unstructured text data.

In this project I use unsupervised learning techniques to identify different segments of costumers with different preferences for optimizing product delivery.

Analyze customers using unsupervised learning, PCA and K-Mean Clustering of Arvato dataset

In this project I have used unsupervised learning techniques to see if any similarities exist between customers, and how to best segment customers into distinct categories using a real-world dataset

Udacity DSND capstone project on the Bertelsmann-Arvato challenge on customer segmentation report and supervised learning model.

code for Visualizing and Understanding the Relationship between PCA, Auto encoder and K-Means Clustering.

Project on real-time proprietary data for Bertelsmann Arvato Analytics to identify customer segments that form the core customer base of the company using unsupervised learning techniques. Data cleaning was an integral part of the project since the data used here was real-world. Techniques like Principal Component Analysis were also used for Dim…

A study in K-Means clustering and MLP methods for digit recognition and classification.

This dataset from "ShufersalML" captures customer order history, aiming to predict future purchases using Python. It involves interconnected files that detail customer orders over time. The goal is to build a predictive model leveraging past order patterns to anticipate which products a user is likely to include in their next order.

[R] Unsupervised Learning with K-median Clustering

Tugas akhir mata kuliah Data Mining

Ipny and HTML files EDA Case Studies