cophenetic-distance

The project involves performing clustering analysis (K-Means, Hierarchical clustering, visualization post PCA) to segregate stocks based on similar characteristics or with minimum correlation. Having a diversified portfolio tends to yield higher returns and face lower risk by tempering potential losses when the market is down.

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• Jupyter Notebook

全球新冠肺炎的数据分析，包括基础知识有：kmeans算法设计，SSE算法设计，分级聚类算法设计，cophenetic distance 算法设计。

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• Python

To identify different segments in the existing customer, based on their spending patterns as well as past interaction with the bank, using clustering algorithms, and provide recommendations to the bank on how to better market to and service these customers.

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• Jupyter Notebook

This project explores and analyzes financial data of a number of securities, applies Hierarchical and K-means clustering to group securities and create cluster profiles to develop personalized portfolios and investment strategies for clients

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• Jupyter Notebook

Using Hierarchial clustering to categories the spending of customers into groups based on their spending habit and other features

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• Jupyter Notebook

An investment advisory firm needs to segment stock offerings so they may offer their customers understandable investment options.

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Project involves performing clustering analysis (K-Means, Hierarchical clustering, visualization post PCA) to segregate stocks based on similar characteristics or with minimum correlation. Having a diversified portfolio tends to yield higher returns and faces lower risk by tempering potential losses when the market is down.

• Updated
• Jupyter Notebook

Analyze the stocks data, grouping the stocks based on the attributes provided, and sharing insights about the characteristics of each group.

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• Jupyter Notebook