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1. Medium-Post-1-Exploratory-Analysis-of-YouTube-Statistics Medium-Post-1-Exploratory-Analysis-of-YouTube-Statistics Public

   This is code for my exploratory of analysis of YouTube Statistics to determine which metrics influence channel revenue most. A DataFrame is created, and multiple groupby functions with various feat…

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2. Medium-Post-2-Network-Analysis-of-Amazon-Product-Metadata Medium-Post-2-Network-Analysis-of-Amazon-Product-Metadata Public

   This is a network analysis of Amazon product metadata that creates nodes out of product ASIN's and edges out of their co-purchases. Calculations are done for in-degree centrality for each node to d…

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3. Medium-Post-3-Computing-Twitter-Account-Similarity Medium-Post-3-Computing-Twitter-Account-Similarity Public

   This is an analysis of Twitter posts and account engagement metrics to uncover which regular accounts are most similar to popular accounts using cosine similarity. The data is from the Bright Data …

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4. Medium-Post-4-Clustering-Credit-Card-Usage-Behavior Medium-Post-4-Clustering-Credit-Card-Usage-Behavior Public

   This is an analysis of credit card data that clusters data points by usage behavior using K-means (unsupervised machine learning algorithm). To find the optimal value of k, the elbow method is done…

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5. Medium-Post-5-Classifying-Spam-with-Multinomial-Bayes-Theorem Medium-Post-5-Classifying-Spam-with-Multinomial-Bayes-Theorem Public

   This is an analysis of SMS texts from the UCI Machine Learning Repository. Supervised learning is performed with a model (Multinomial NB) from sklearn.naive_bayes. It is trained and tested using th…

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