
Deep Learning Basics with Python, TensorFlow and Keras - mrleinad
https://pythonprogramming.net/introduction-deep-learning-python-tensorflow-keras/
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stared
Sigh, I know there is interest in learning, but there are a few things that
(IMHO) don't follow the best practices.

For example - pickle for saving numerical data. Please, use h5py. Pickle can
save any Python objects... and execute any (also - not-python) code. Or in
general - you load a pickle, and cannot guess what had happened. With h5py -
you have a tree of numerical objects, nothing more, nothing less.

Fo those reasons, I use pickle only when there is no other way to go - i.e.
Python objects that cannot be serialized into anything language-agnostic. For
saving purely numerical data, h5py is my way to go
([http://docs.h5py.org/en/latest/quick.html](http://docs.h5py.org/en/latest/quick.html)).

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lelima
Check out Jeremy Howard and Fastai. I like sentex, their videos are good, but
Jeremy is another level.

[http://course.fast.ai/index.html](http://course.fast.ai/index.html)

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sremani
I have used this website when I had itch about doing Monte-Carlo. I went
through the course at a good pace. The beauty was you can follow the video or
the text or both depending on your style of learning.

I will definitely check the deep learning course.

note: I am not a python programmer.

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Insanity
Can anyone recommend good books for learning deep learning with python?

~~~
stared
For a very practical introduction to deep learning with Keras, I recommend
Deep Learning with Python by François Chollet,
[https://www.manning.com/books/deep-learning-with-
python](https://www.manning.com/books/deep-learning-with-python).

For a general context, my post "Learning Deep Learning with Keras"
[https://p.migdal.pl/2017/04/30/teaching-deep-
learning.html](https://p.migdal.pl/2017/04/30/teaching-deep-learning.html) or
for a practical quick start - "Starting deep learning hands-on: image
classification on CIFAR-10" [https://deepsense.ai/deep-learning-hands-on-
image-classifica...](https://deepsense.ai/deep-learning-hands-on-image-
classification/).

~~~
Insanity
Thank you!

In general I prefer reading technical material (to really learn something)
from a piece of paper rather than from a screen. I'll order the book :)

~~~
screye
Try the CS231n course from Stanford. Assignments, solutions, slides and
lectures are available. Proper grad level deep learning course with excellent
notes. The assignments are IMO, the best way to get good and in-depth
knowledge of deep learning.

For books, Ian Goodfellow's deep learning is the best theory (as theoretical
as Deep Learning gets ) oriented book.

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shawn
I know a machine learning engineer from a certain massive lending company. I
asked him “How do you decide which strategy to use and which algorithms to pay
attention to? There are so many, and it’s hard to figure out which ones are
production grade.”

He said gradient boosting. I pointed out that that implies there would be some
period of time where the algorithm makes bad decisions. He said yup, that’s
why it’s hard to start a lending company. Gotta find the data on the bad
performers.

Apparently their original decision model was just a hand crafted set of if-
statements.

I suspect most ML endeavors that seem impressive have origin stories like
that, but it’s only anecdata.

~~~
kgwgk
> He said gradient boosting. I pointed out that that implies there would be
> some period of time where the algorithm makes bad decisions.

How are the first and second sentences related? Would other algorithms make
better decisions?

~~~
shawn
Sure, self-play. Generate the data and search through the problem space for
optimal decisions before they come up.

