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Simple Perceptron example? #9

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joeyklee opened this issue Sep 4, 2019 · 3 comments
Open

Simple Perceptron example? #9

joeyklee opened this issue Sep 4, 2019 · 3 comments
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@joeyklee
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joeyklee commented Sep 4, 2019

For me one of the "ah-ha" moments was seeing what is going on in a Perceptron. Seeing how simple "intelligence" can be was very helpful to demystify the idea of defining fitness.

@joeyklee joeyklee added enhancement New feature or request content labels Sep 4, 2019
@shiffman
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shiffman commented Sep 5, 2019

I was thinking this material would be part of week 4 - DIY neural nets (which is my theoretical deadline for a rewrite of this chapter), but I could cover / assign the first section on the perceptron earlier.

@joeyklee
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joeyklee commented Sep 5, 2019

@shiffman - excellent! That's great to hear. I think it makes sense to have it in week 4 unless it is too much to pack into 1 week.

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There is a lot to do this week so I'm not sure if a full discussion of the Perceptron fits. I wonder if it might work well to double back into some of the details next week when we look at a second round of examples with the DIY neural network. I got lost in tensors this weekend so didn't get to make major revisions to chapter 10 yet. I should at a minimum add some links to #39

shiffman added a commit that referenced this issue Sep 23, 2019
shiffman added a commit that referenced this issue Sep 23, 2019
* skeleton of week 4 README

* moving and editing material from google doc syllabus

* Update 04_diy_neural_network/README.md

Co-Authored-By: Ellen Nickles <[email protected]>

* Update 04_diy_neural_network/README.md

Co-Authored-By: Ellen Nickles <[email protected]>

* adding video tutorials, moving new ImageNet works

The new ImageNet works suggested by @ellennickles  are excellent. I am  going to put them with the ImageNet materials from earlier weeks since they match with that material better (this week is about non-image data) and then highlight them in class.

* adding Excavating AI work thanks to @ellennickles

* while i'm at it, adding Humans of AI by @philippschmitt

* adding wattenberg and viegas talk #29

* adding nature of code chapter 10 #9

* removing two articles to reduce load

could consider adding these back in later or somewhere else, etc. The nature.com article includes a lot of sophisticated statistics and math concepts / notation so is likely be beyond the scope of this course.

cc @lydiajessup

* [How to Make A.I. That’s Good for People](https://www.nytimes.com/2018/03/07/opinion/artificial-intelligence-human.html) by Fei-Fei Li
* [Estimating the success of re-identifications in incomplete datasets using generative models](https://www.nature.com/articles/s41467-019-10933-3) from nature.com

* ready for merge, still lots of work to do
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