Math Workshop: From Kindergarten to Deep Learning

Apr 22, 2018 · New York, United States of America

We will be going through the entire Khan Academy Math track.

Starting at kindergarten, we will move through algebra, reaching calculus, statistics and probability and finally to Linear Algebra. The purpose of this is to get a firm understanding of the maths behind machine learning and data science. Then we will read the book The Elements of Statistical Learning and Deep Learning by Bengio, et al.

Once this is accomplished, the more advanced people will form a group to start reading the Machine Intelligence Research Institute's suggested reading list. The purpose of this will be to prepare those interested in doing advanced AI research.

We will begin to form the core of a MIRIx Workshop in NYC.
See: https://intelligence.org/research-guide/

Ambitious. Yes. But, let's just take it one day at a time.

The price is to raise money for the meetup to continue to offer services to develop the med tech and AI community in NYC. Its a tall proposition to pay to study math! However, the people who will show up will be motivated and that is who you wish to study with. Also, those who pay can stick around for the Python workshops right after.

If we get sponsorship from MIRI, we work to eliminate the price.

Note: I am not going to be teaching you. We will use Khan academy and this will be a peer to peer learning group. But, I will be organizing it ensure that its focused and effective.

Event organizers
  • New York Artificial Intelligence In Healthcare

    Interested in AI? Join our group! This group is dedicated to the application of neuroscience, artificial intelligence, medicine, and computer science towards the further understanding and development of artificial intelligence. We also focus on developing the New York MedTech industry.   The goal is to create a laid back place where the spirit of the coffeehouse culture of the Enlightenment meets the modern hackerspace; where people from different disciplines who wouldn't normally meet can exchange ideas,

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