Add notebook for chapter 13, loading and preprocessing data

main
Aurélien Geron 2019-03-14 09:15:09 +08:00
parent af3f11dbc9
commit 990fb1a453
2 changed files with 1758 additions and 22 deletions

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##### Core scientific packages
jupyter==1.0.0
matplotlib==3.0.2
numpy==1.15.4
pandas==0.23.4
scipy==1.2.0
jupyter-client==5.2.4
jupyter-console==6.0.0
jupyter-core==4.4.0
matplotlib==3.0.3
numpy==1.16.2
pandas==0.24.1
scipy==1.2.1
##### Machine Learning packages
scikit-learn==0.20.2
scikit-learn==0.20.3
# Optional: the XGBoost library is only used in the ensemble learning chapter.
xgboost==0.81
xgboost==0.82
##### Deep Learning packages
# Replace tensorflow with tensorflow-gpu if you want GPU support. If so,
# you need a GPU card with CUDA Compute Capability 3.0 or higher support, and
# you need a GPU card with CUDA Compute Capability 3.5 or higher support, and
# you must install CUDA, cuDNN and more: see tensorflow.org for the detailed
# installation instructions.
tf-nightly-2.0-preview
#tf-nightly-gpu-2.0-preview
#tensorflow==1.12.0
#tensorflow-gpu==1.12.0
#tensorflow-hub==0.2.0
#tensorflow-probability==0.5.0
tb-nightly
#tensorflow-hub
#tensorflow-probability
# Optional: OpenAI gym is only needed for the Reinforcement Learning chapter.
# There are a few dependencies you need to install first, check out:
# https://github.com/openai/gym#installing-everything
#gym[all]==0.10.9
#gym[all]
# If you only want to install the Atari dependency, uncomment this line instead:
#gym[atari]==0.10.9
#gym[atari]
##### Image manipulation
imageio==2.4.1
Pillow==5.3.0
scikit-image==0.14.1
imageio==2.5.0
Pillow==5.4.1
scikit-image==0.14.2
##### Extra packages (optional)
# Nice utility to diff Jupyter Notebooks.
#nbdime==1.0.4
#nbdime
# May be useful with Pandas for complex "where" clauses (e.g., Pandas
# tutorial).
@ -79,8 +81,8 @@ numexpr==2.6.9
# Optional: these libraries can be useful in the classification chapter,
# exercise 4.
nltk==3.4
urlextract==0.8.3
urlextract==0.9
# Optional: this extension is handy to easily start/stop tensorboard
# server(s) directly from Jupyter.
#jupyter-tensorboard==0.1.8
# Optional: tqdm displays nice progress bars, ipywidgets for tqdm's notebook support
tqdm==4.31.1
ipywidgets==7.4.2