

Machine Learning: How Did We Get Here?
Tom Mitchell | Stanford Digital Economy Lab | Carnegie Mellon University
Tom Mitchell literally wrote the book on machine learning. In this series of candid conversations with his fellow pioneers, Tom traces the history of the field through the people who built it. Behind the tech are stories of passion, curiosity, and humanity.
Tom Mitchell is the University Founders Professor at Carnegie Mellon University, a Digital Fellow at the Stanford Digital Economy Lab, and the author of Machine Learning, a foundational textbook on the subject. This podcast is produced by the Stanford Digital Economy Lab.
Tom Mitchell is the University Founders Professor at Carnegie Mellon University, a Digital Fellow at the Stanford Digital Economy Lab, and the author of Machine Learning, a foundational textbook on the subject. This podcast is produced by the Stanford Digital Economy Lab.
Top mentioned books
Here are the most frequently recommended books on the Machine Learning: How Did We Get Here? podcast:

#1 Mentioned in 2 episodes
Perceptrons

#2 Mentioned in 2 episodes
Parallel Distributed Processing
Explorations in the Microstructure of Cognition: Foundations

#3 Mentioned in 1 episodes
The Structure of Scientific Revolutions

#4 Mentioned in 1 episodes
Classification and Regression Trees
1st Edition
#5 Mentioned in 1 episodes
A Theory of the Learnable

#6 Mentioned in 1 episodes
Statistical Learning Theory

#7 Mentioned in 1 episodes
Elements of Information Theory
Wiley Series in Telecommunications and Signal Processing

#8 Mentioned in 1 episodes
The Elements of Statistical Learning
Data Mining, Inference, and Prediction
















