Use Analytic Solver Data Science to make predictions using machine learning, statistical forecasting and text mining

Forecasting (for time series data like sales or stock prices) and data mining or machine learning (for all kinds of data) helps you find explanatory features and patterns -- even in free-form text -- and "train" models to accurately classify or predict new cases. Here are some examples:

  • Predicting which subscription customers are likely to "churn"
  • Deciding whether to approve and fund mortgage applications
  • Displaying products of interest to online shoppers
  • Checking credit card transactions for fraud
  • Timing equipment maintenance ahead of predicted failures
  • Measuring positive or negative sentiment in social media comments
  • Detecting seasonal patterns in demand to make better forecasts

To learn more, visit these tutorials:

  1. Using Classification Trees – a popular machine learning method.

  2. Using Neural Networks – the most basic form of "deep learning".

  3. Predicting Flight Delays – a "Big Data" case study using the FAA airline dataset.

  4. New York City Taxi Fares – exploring a public dataset to find tipping patterns.