CSE012/CS059 – Data Mining Fall 2024

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Tutorial Slides For the material for these tutorials, many thanks to: Evimaria Terzi, Mark Corvella, and Aris Anagnostopoulos. Tutorial 1: Introduction to discrete probabilities. (pptx, pdf) Thanks to Aris Anagnostopoulos for the slides. Part I from the book All of Statistics by Larry A. Wasserman Tutorial 2: Introduction to notebooks. Python reminders. Slides: pptx, pdf Instructions to set up Google Colab (pdf) Notebook with Python Reminders (ipynb, html) Τutorial 3: Introduction to the Pandas library  (ipynb, html) The files for the notebooks Notes from the class of Evimaria Terzi and Mark Crovella Τutorial 4: Libraries for statistical analysis and plotting Notebook for Plotting, Statistical Analysis (ipynb, html) The file example-functions.csv Notes from the class of Evimaria Terzi and Mark Crovella Tutorial 5: Introduction to the Numpy and SciPy libraries for matrix manipulation (ipynb, html). Tutorial 6: Libraries for data preprocessing (ipynb, html) Τutorial 7:Introduction to the SciKit-Learn (sklearn) library for clustering (ipynb, html) Tutorial 8: Introduction to the scikit-learn library and applications to classification. The gensim library and word embeddings. (Notebook: ipynb, html). Tutorial 9: Introduction to the library NetworkX (Notebook: ipynb, html). The graph_edges.txt file The graph-example.txt file The karate.gml file