elbow-curves

Unsupervised Machine Learning analysis to find patterns in Cryptocurrencies market valuations.

The objective of this project is to categorise the countries using some socio-economic and health factors that determine the overall development of the country and then accordingly suggest the NGO the country which is in dire need of help.

We created a report that includes what cryptocurrencies are on the trading market and how they could be grouped to create a classification system for this new investment.The data Martha provided us was not ideal, so we processed to fit the machine learning models. Since there is no known output for what Martha is looking for, we decided to use u…

This project collects product data from Flipkart using web scraping techniques and performs data cleaning,exploratory data analysis,and machine learning modeling to extract meaningful business insights.The results are visualized using Power BI dashboards to analyze pricing trends,product ratings,reviewsand discount strategies in the e-commerce str.

This project analyzes customer behavior in online retail using cohort analysis, **Recency, Frequency, Monetary (RFM)** metrics, and K-means clustering to segment customers. It identifies key groups like Best, At-Risk, and Average Customers, offering strategies to enhance engagement and drive loyalty.

Using k-Means algorithm and a Principal Component Analysis (PCA) to cluster cryptocurrencies.

K-means clustering of texts (survey answers) using word-embeddings, finding optimal elbow-point, and averaging multiple-word expressions.

Used machine learning techiques to cluster and visualize cryptocurrency data.

This un-supervised machine learning project applies unsupervised clustering to customer records from a grocery firm's database to segment customers based on their behavior. It includes data preprocessing, exploratory data analysis, and K-Means clustering to uncover meaningful insights.

Unsupervised machine learning models used to group the cryptocurrencies to help prepare for a new investment.

Application of unsupervised learning to create a classification system for cryptocurrencies.

Unsupervised Machine Learning Technique - KMeans Clustering to classify cryptocurrency data using Principle Component Analysis (PCA)to to reduce the number of dimensions of the scaled data.

Machine learning with elbow curves and K-Means model

Use unsupervised machine learning techniques to analyze cryptocurrency data.

Unsupervised Learning

This project is about creating a report that includes what cryptocurrencies are on the trading market and how they could be grouped to create a classification system for a new investment.

Used unsupervised machine Learning predictive algorithm to analyze the investment prospects and tendencies of cryptocurrencies.

An unsupervised learning algorithm that K-Means clustering with feature scaling, WCSS/Inertia, Elbow Method, and cluster visualization.