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1. Building a K-means Clustering Model for Population A/B Testing With BigQuery | by Marie Lefevre | Mar, 2021 | Towards Data Science

   2021-03-10 Tags: k-means, clustering, a b testing by klotz
2. Analysis of crimes in Mexico during 2017 with Machine Learning techniques (Cluster Analysis): Comparison Elbow Method and Silhouette Method | by Isaac Arroyo | Nov, 2020 | Towards Data Science

   2020-11-22 Tags: machine learning, k-means, silhouette, elbow, crime, exploratory data analysis, mexico by klotz
3. Cluster-then-predict for classification tasks - Towards Data Science

   2020-02-11 Tags: clustering, prediction, k-means, feature engineering, machine learning by klotz
4. K-Means & Other Clustering Algorithms: A Quick Intro with Python – LearnDataSci

   2019-02-01 Tags: machine learning, clustering, python, examples, spectral, k-means, agglomerative, zachary karate, example by klotz
5. How I used machine learning to classify emails and turn them into insights (part 1).

   2018-11-07 Tags: machine learning, tf-idf, k-means, text, nlp, classifier, email by klotz
6. Applying Machine Learning to classify an unsupervised text document

   2018-11-03 Tags: machine learning, nlp, tf-idf, classification, k-means, blog by klotz
7. Comparing the performance of non-supervised vs supervised learning methods for NLP text…

   2018-10-19 Tags: nlp, machine learning, tf-idf, classification, k-means, pca, lda by klotz
8. “Understanding K-means Clustering in Machine Learning”

   2018-09-13 Tags: k-means, clustering, python, machine learning by klotz
9. Document Clustering with Python

   tokenizing and stemming each synopsis
   transforming the corpus into vector space using tf-idf
   calculating cosine distance between each document as a measure of similarity
   clustering the documents using the k-means algorithm
   using multidimensional scaling to reduce dimensionality within the corpus
   plotting the clustering output using matplotlib and mpld3
   conducting a hierarchical clustering on the corpus using Ward clustering
   plotting a Ward dendrogram
   topic modeling using Latent Dirichlet Allocation (LDA)

   2018-08-16 Tags: lda, document, clustering, python, tf-idf, k-means, nlp, text by klotz
10. Top 100 Films

    ow can you learn about the underlying structure of documents in a way that is informative and intuitive? This basic motivating question led me on a journey to visualize and cluster documents in a two-dimensional space. What you see above is an output of an analytical pipeline that begin by gathering synopses on the top 100 films of all time and ended by analyzing the latent topics within each document. In between I ran significant manipulations on these synopses (tokenization, stemming), transformed them into a vector space model (tf-idf), and clustered them into groups (k-means). You can learn all about how I did this with my detailed guide to Document Clustering with Python. But first, what did I learn?

    2016-06-02 Tags: lda, nlp, clustering, k-means, cosine similarity, imdb, movies, tf-idf by klotz

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