The-Analytics-Edge

R Markdown notes of the edX/MIT MOOC Course The Analytics Edge

These are published under my RPubs repository

• Table of Contents
• Unit 1 : An Introduction to Analytics
  • Unit 1 : An Analytical Detective
  • Unit 1 : Stock Dynamics
  • Unit 1 : Demographics and Employment in the United States
• Unit 2 : Linear Regression
  • Unit 2 : Moneyball
  • Unit 2 : NBA
  • Unit 2 : Climate Change
  • Unit 2 : Reading Test Scores
  • Unit 2 : Detecting Flu Epidemics via Search Engine Query Data
• Unit 3 : An Introduction to Logistic Regression
  • Unit 3 : Evaluating Risk Factors to Save Lives
  • Unit 3 : Predicting the Winner Before any Votes are Cast
  • Unit 3 : Popularity of Music Records
  • Unit 3 : Predicting Parole Violators
  • Unit 3 : Predicting Loan Repayment
• Unit 4 : An Introduction to Trees
  • Unit 4 : Keeping An Eye on Healthcare Costs
  • Unit 4 : Regression Trees for Housing Data
  • Unit 4 : Understanding Why People Vote
  • Unit 4 : Letter Recognition
  • Unit 4 : Predicting Earnings from Census Data
• Unit 5 : An Introduction to Text Analytics
  • Unit 5 : Predictive Coding
  • Unit 5 : Detecting Vandalism on Wikipedia
  • Unit 5 : Automating Reviews in Medicine
  • Unit 5 : Separating Spam from Ham (Part 1)
• Unit 6 : An Introduction to Clustering
  • Unit 6 : Clustering to Better Predict Heart Attacks
  • Unit 6 : Segmenting Images to Create Data
  • Unit 6 : Document Clustering with Daily Kos
  • Unit 6 : Market Segmentation for Airlines
  • Unit 6 : Predicting Stock Returns with Cluster-Then-Predict
• Unit 7 : An Introduction to Visualization
  • Unit 7 : Visualization for Law and Order
  • Unit 7 : The Good, the Bad, and the Ugly
  • Unit 7 : Election Forecast Revisted
  • Unit 7 : Visualizing Network Data
  • Unit 7 : Visualizing Text Data Using World Clouds
• Unit 8 : An Introduction to Linear Optimization
  • Unit 8 : Radiation Therapy
  • Unit 8 : Google Adwords
  • Unit 8 : Investment Management under Taxation
  • Unit 8 : Filatoi Riuniti
  • Unit 8 : Gasoline Blending
• Unit 9 : An Introduction to Integer Optimization
  • Unit 9 : eHarmony
  • Unit 9 : Operating Room Scheduling
  • Unit 9 : Selecting Profitable Hotel Sites
  • Unit 9 : Assigning Sales Regions at Pfizer Turkey
  • Unit 9 : Class Assignments in an Elementary School
• Final Exam : Estimating AirBnB Prices
• Final Exam : Predicting Customer Churn
• Final Exam : Understanding Movie Preferences

-Sulman Khan