submissions

your homeworks

homework 1

  • review and data exploration
  • assigned: january 11
  • due date: january 18

homework 2

  • market basket analysis and association rules
  • assigned: january 18
  • due date: january 25

homework 3

  • mastering map reduce
  • assigned: september 26
  • due date: october 10

homework 4

  • clustering and parameter estimation
  • assigned: february 8
  • due date: february 15

homework 5

  • bayes rules and ml toolboxes
  • assigned: february 15
  • due date: february 22

homework 6

  • classifier evaluation metrics
  • assigned: february 22
  • due date: march 28

homework 7

  • deep learning and the keras toolbox
  • assigned: march 28
  • due date: april 11 (optional)


your project



in-class colabs

week 1 colabs

  • In-Class
    Introducing Google Colabs
    Review and Calibration

week 2 colabs

  • In-Class
    Introducing Docker and Docker Containers
    Industry Practice of Containerization

week 3 colabs

  • In-Class
    Counting Shakespeare's Words
    Basic Spark and RDD's
  • Setup
    Setup for Homework 3 - PySpark
    Spark Data Ingestion

week 4 colabs

  • In-Class
    Multi-source Joins
    Joining from multiple data sources with text

week 5 colabs

  • In-Class
    Principle component analysis
    Practice with power iterations to identify principle components

week 6 colabs

  • In-Class
    Anomaly Detection
    Colab using Naïve Bayes to predict outliers

week 11 colabs

  • In-Class
    Mining Structured Data and Images
    Manually coding logistic regression optimization

week 12 colabs

  • In-Class
    Using Keras and Traditional Text Mining
    Fun diffusion models, the MNIST convolutional network, and TF/IDF practice