When Machine Learning Fails…

Christopher Teixeira
January 25, 2023

A little about me…


Christopher Teixeira

Principal Data Scientist

The MITRE Corporation



Interests

  • Data Analytics
  • Applied Statistics
  • Operations Research

Education

  • MS in Operations Research, George Mason University
  • BSc in Mathematics, Worcester Polytechnic Institute

What is machine learning?

Machine Learning is the study of computer algorithms that improve automatically through experience. Applications range from data mining programs that discover general rules in large data sets to information filtering systems that automatically learn users’ interests.


Supervised Learning

Unsupervised Learning

Reinforcement Learning

What can it be used for?


Supervised Learning

  • Determine the likelihood of buying an item
  • Translating handwriting
  • Tomorrow’s weather forecast
  • Sending incoming email to a SPAM folder
  • Predicting sale price for a house

Unsupervised Learning

  • Customer segmentation
  • Simplify complex feature sets
  • Anomaly detection
  • Recommender systems
  • Determine communities in a social network
  • Identify topics covered across a series of documents

Reinforcement Learning

  • Autonomous driving
  • Automated stock trading
  • Dynamic medical diagnoses and treatments
  • Artificial players in games
  • Dynamic recommender systems
  • Serving up real-time advertising

What can it be used for?


Supervised Learning

  • Determine the likelihood of buying an item
  • Translating handwriting
  • Tomorrow’s weather forecast
  • Sending incoming email to a SPAM folder
  • Predicting sale price for a house

Unsupervised Learning

  • Customer segmentation
  • Simplify complex feature sets
  • Anomaly detection
  • Recommender systems
  • Determine communities in a social network
  • Identify topics covered across a series of documents

Reinforcement Learning

  • Autonomous driving
  • Automated stock trading
  • Dynamic medical diagnoses and treatments
  • Artificial players in games
  • Dynamic recommender systems
  • Serving up real-time advertising

What can it be used for?


Supervised Learning

  • Determine the likelihood of buying an item
  • Translating handwriting
  • Tomorrow’s weather forecast
  • Sending incoming email to a SPAM folder
  • Predicting sale price for a house

Unsupervised Learning

  • Customer segmentation
  • Simplify complex feature sets
  • Anomaly detection
  • Recommender systems
  • Determine communities in a social network
  • Identify topics covered across a series of documents

Reinforcement Learning

  • Autonomous driving
  • Automated stock trading
  • Dynamic medical diagnoses and treatments
  • Artificial players in games
  • Dynamic recommender systems
  • Serving up real-time advertising

What can it be used for?


Supervised Learning

  • Determine the likelihood of buying an item
  • Translating handwriting
  • Tomorrow’s weather forecast
  • Sending incoming email to a SPAM folder
  • Predicting sale price for a house

Unsupervised Learning

  • Customer segmentation
  • Simplify complex feature sets
  • Anomaly detection
  • Recommender systems
  • Determine communities in a social network
  • Identify topics covered across a series of documents

Reinforcement Learning

  • Autonomous driving
  • Automated stock trading
  • Dynamic medical diagnoses and treatments
  • Artificial players in games
  • Dynamic recommender systems
  • Serving up real-time advertising

Machine learning examples

Machine learning can be pretty amazing

Search and rescue with airborne optical sectioning

Source: Nature.com

Machine learning can be pretty amazing

Using Data to Create Paths out of Homelessness