Learning Machine Learning
summary
Covers concrete recipes and working code: a Naive Bayes classifier in ~78 lines of code that classifies English vs French, a live Twitter sentiment stream that scores tweets -5 to +5, and a toy genetic algorithm that repeatedly evolves arrays until it finds four numbers summing to 200—often within a few hundred generations (examples show 256 and 96). Code is provided in JavaScript and PHP on GitHub, demos run live and the classifiers and GA actually converge.
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chapters (19)
- 0:00Intro
- 3:45About me
- 4:08Our office
- 5:00Agenda
- 5:26Artificial Intelligence
- 6:01What is Artificial Intelligence
- 9:10What is Machine Learning
- 11:19Microsoft Bot
- 13:13Deep Learning
- 15:56Unsupervised
- 16:49Knavebased classifier
- 17:08Bayes theorem
- 18:06Nuts in chocolate
- 19:39Classification
- 20:45Demo
- 28:44Genetic Algorithm
- 29:51How does it work
- 31:17Autodesk Dreamcatcher
- 37:49Academic Example
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