Data Science: Principles and Python

Unit 1: Exploring Data

• Introduction
  • The Data Scientist
  • Why Python?
  • Installation and Workflow
  • This Book
• Data and Computation
  • Two Tales of Data
  • Data in Python
  • Processing Data, Latency, and Iterables
  • Data Structures and Dictionaries
• Statistical Learning Machines
  • The Prediction Perspective
  • Numpy and Vectorization
  • Supervised Learning
• Data Wrangling
  • Introduction to Pandas
  • Wrangling data with indices
  • Missingness
• Data Visualization
  • Deconstructing the simple plot
  • Matplotlib
  • Grammar of graphics
  • Excellence and Integrity in Graphics
• Case Study: US College Scorecard
  • Reading in the data
  • The rise in tuition
  • Earnings trends
  • Other comparisons

Unit 2: Learning from Complex Data

• Classification
• Collecting and Managing Data
• Structured Text Data
• Interactive Visualization

Unit 3: Machine Learning

• Statistical Inference
• Factor Models and Eigensystems
• Optimization for Machine Learning
• Network and Relational Data

Unit 4: Advanced Machine Learning

• Interactive Machine Learning
• Distributed Statistical Learning
• Image Data and Computer Vision
• Natural Language Processing

Indices and tables

• Index
• Module Index
• Search Page