Computational Approaches and Implemntation

Objective

  • Introduction to algorithms of processing of Big Data by using Python

Textbook

Learning Data Mining with Python, Robert Layton, Packt, 2015

  • 1. Getting Started with Data Mining
  • 2. Classifying with scikit-learn Estimators
  • 3. Predicting Sports Winners with Decision Trees
  • 4. Recommending Movies Using Affinity Analysis
  • 5. Extracting Features with Transformers
  • 6. Social Media Insight Using Naïve Bayes
  • 7. Discovering Accounts to Follow Using Graph Mining Loading the dataset
  • 8. Beating CAPTCHAs with Neural Networks
  • 9. Authorship Attribution
  • 10. Clustering News Articles
  • 11. Classifying Objects in Images Using Deep Learning
  • 12. Working with Big Data

Machine Learning in Python, Michael Bowles, Wiley, 2015

  • 1. The Two Essential Algorithms for Making Predictions
  • 2. Understand the Problem by Understanding the Data
  • 3. Predictive Model Building: Balancing Performance, Complexity, and Big Data
  • 4. Penalized Linear Regression
  • 5. Ensemble Methods
  • 6. Building Ensemble Models with Python