cs501r_f2016
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| - | ====CS501r, Fall 2016 - Deep Learning: Theory and Practice==== | ||
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| - | [[cs501r_f2016:desc|Here is the course description.]] | ||
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| - | === Labs === | ||
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| - | [[cs501r_f2016:lab_notes|General notes on ipython and seaborn]] | ||
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| - | [[cs501r_f2016:lab1|Lab 1 - Anaconda and playground screenshot]] | ||
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| - | [[cs501r_f2016:lab2|Lab 2 - Perceptron]] | ||
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| - | [[cs501r_f2016:lab3|Lab 3 - Sigmoid derivative]] | ||
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| - | [[cs501r_f2016:lab4|Lab 4 - Automatic differentiation]] | ||
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| - | [[cs501r_f2016:lab5|Lab 5 - Tensorflow image classifier]] | ||
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| - | [[cs501r_f2016:lab6|Lab 6 - Optimization zoo 1]] | ||
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| - | [[cs501r_f2016:lab7|Lab 7 - Optimization zoo 2]] | ||
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| - | [[cs501r_f2016:lab8|Lab 8 - Feature zoo 1]] | ||
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| - | [[cs501r_f2016:lab9|Lab 9 - Feature zoo 2]] | ||
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| - | [[cs501r_f2016:lab10|Lab 10 - RNNs, LSTMs, GRUs]] | ||
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| - | [[cs501r_f2016:lab11|Lab 11 - Tensor factorization]] | ||
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| - | [[cs501r_f2016:lab12|Lab 12 - Deep RL]] | ||
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| - | [[cs501r_f2016:lab13|Lab 13 - Inceptionism]] | ||
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| - | [[cs501r_f2016:lab14|Lab 14 - Variational autoencoder]] | ||
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| - | [[cs501r_f2016:lab15|Lab 15 - Highway nets and resnets]] | ||
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| - | [[cs501r_f2016:fp|Final project]] | ||
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cs501r_f2016.txt ยท Last modified: 2021/06/30 23:42 (external edit)
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