Lesson 8 in-class

Part 2 (2017)
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Does prisma app use something similar to come up with these cool filters?

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Where can I find the Jupyter theme Jeremy is using?

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77

Is it better to calculate f_content for a higher layer for VGG and use a lower layer for f_style sine the higher layer abstracts are captured in the higher layer and the lower layer captures textures and “style”?

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http://www.platform.ai/part2/lesson1/neural-style.ipynb

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@nikesh Jupyter color themes: https://github.com/dunovank/jupyter-themes

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80

i had an error running it, did anyone else have this issue?

ModuleNotFoundError: No module named 'xgboost'

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@mo.shakirma I had to install these to get the notebooks running

pip install xgboost
pip install gensim
pip install keras-tqdm

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@mo.shakirma pip install xgboost

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I shared a link on the part 1 forum. anyway here it is: https://github.com/dunovank/jupyter-themes

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for me it was:

pip install matplotlib
pip install pandas
pip install xgboost
pip install bcolz
pip install gensim
pip install nltk
pip install keras_tqdm

from utils2 import * caused all that dependencies

3 Likes
85

I found out about Part I of this course from Import AI.

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86

If you import the VGG model that is built into keras (keras.applications), do you still have to re-order the channels, etc.?

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https://docs.scipy.org/doc/numpy/user/basics.broadcasting.html

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88

I like the Import AI and Wild ML newsletters: http://www.wildml.com/newsletter/

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89

Shouldn’t we use something like Resnet instead of VGG (with avg pooling) since the residual blocks carry more context?

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Should/do we put in batch normalization like we did in lesson 5?

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Will the pre-trained weights change if we’re using Average pooling instead of max pooling?

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92

how about vgg16_bn_avg?

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MaxPool --> AvgPool change still preserves the “pretrained”?

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Do you have to retrain VGG on imagenet when you change max pooling to avg pooling?