Incorporated unsupervised machine learning, PCA algorithm, and K-Means clustering to analyze and classify a database of cryptocurrencies.
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Updated
Jan 31, 2022 - Jupyter Notebook
Incorporated unsupervised machine learning, PCA algorithm, and K-Means clustering to analyze and classify a database of cryptocurrencies.
Employing unsupervised learning techniques to cluster Italian wines grown by three different cultivars
NETFLIX MOVIES AND TV SHOWS CLUSTERING is a project that aims to cluster the available movies and TV shows on Netflix based on their attributes such as genre, release year, and country of production.
Use unsupervised machine learning, PCA algorithm, and K-Means clustering to analyze and classify a database of cryptocurrencies.
Analyzing Cryptocurrency data utilizing unsupervised ML
Stardew Valley: Missed Connections is the thesis project of Meghan Andrews for her Masters of Professional Studies in Information and Data Visualization from Maryland Institute College of Art , completed December 2020
Recommendations on which characteristics are most important for determining whether a customer has a favourable perception of the microvan concept, to segment the market, and to determine which segment(s) would be good to target based on the analysis of data.
Using Unsupervised Machine Learning to examine the outcome of Cryptocurrencies data and how to analyze it.
Exploration of various ML models and techniques for cognitive computing tasks. The primary focus is analysing hidden representations and the effectiveness in classifying data
Data science techniques for pattern recognition, data mining, k-means clustering, and hierarchical clustering, and KDE.
Agglomerative hierarchical clustering on 39.7K female fragrances 🤖
Python implementation of WhatsUp for co-occurring event resolution in social media data
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.
Machine Learning / Multivariate Statistik in Python
Clustering countries from an NGO Data to get Top 10 countries who are in dire need of Aid based on their Socio Economic Condition
performed EDA + clustering analysis
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