Unsupervised Machine Learning analysis to find patterns in Cryptocurrencies market valuations.
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Updated
Jun 18, 2022 - Jupyter Notebook
Unsupervised Machine Learning analysis to find patterns in Cryptocurrencies market valuations.
K-means clustering of texts (survey answers) using word-embeddings, finding optimal elbow-point, and averaging multiple-word expressions.
Using k-Means algorithm and a Principal Component Analysis (PCA) to cluster cryptocurrencies.
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…
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.
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.
Unsupervised Machine Learning
Unsupervised machine learning was used to establish a classification system for actively trading cryptocurrencies for potential investment prospects.
Used machine learning techiques to cluster and visualize cryptocurrency data.
Unsupervised machine learning models used to group the cryptocurrencies to help prepare for a new investment.
Used unsupervised machine Learning predictive algorithm to analyze the investment prospects and tendencies of cryptocurrencies.
Application of unsupervised learning to create a classification system for cryptocurrencies.
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.
Supervised Learning Recap
Unsupervised Machine Learning and Cryptocurrencies
The purpose of this project is to analyze and cluster cryptocurrencies based on their price change percentage over different time periods.
Use unsupervised machine learning techniques to analyze cryptocurrency data
Using unsupervised machine learning algorithms to classify entries in a database of cryptocurrencies.
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