For the next few weeks of AI Show, we are taking a bit of a different tack (let us know if you want more or less of this kind of content). I was invited to present at the Toronto AI User Group in early January and decided to bring along some gear to record the talk. The talk was about an hour long so I split it up into 4 distinct parts to make it more digestible. In this part of the talk I go into three distinct concepts and how they work internally.
- [01:35] What is the difference between AI, Machine Learning, and Deep Learning?
- [04:55] When is Machine Learning an appropriate tool to solve problems?
- [08:28] What is a machine learning model?
Hope you enjoy part 1! As always feel free to send any feedback or add any comments below if you have any questions.
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