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Update environment.yml and requirements.txt

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ageron committed Dec 12, 2019
1 parent 2adec01 commit 2425e98cc3f6a93e1c0931adc384c80d9e2103de
Showing with 96 additions and 101 deletions.
  1. +49 −56 environment.yml
  2. +47 −45 requirements.txt
@@ -1,60 +1,53 @@
name: tf1
channels:
- conda-forge
- defaults
dependencies:
##### Core scientific packages
- python >=3.0
- jupyter==1.0.0
- pip
- matplotlib==3.0.3
- numpy==1.16.2
- pandas==0.24.1
- scipy==1.2.1

##### Machine Learning packages
- scikit-learn==0.20.3
- 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 must install CUDA, cuDNN and more: see tensorflow.org for the detailed
# installation instructions.
- tensorflow==1.13.1
#- tensorflow-gpu==1.13.1

# 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
#- pip:
#- gym[all]==0.10.9
# If you only want to install the Atari dependency, uncomment this line instead:
#- gym[atari]==0.10.9

##### Image manipulation
- imageio==2.5.0
- pillow==6.2.0
- scikit-image==0.14.2

##### Extra packages (optional)
# Nice utility to diff Jupyter Notebooks.
#- nbdime==1.0.5

# May be useful with Pandas for complex "where" clauses (e.g., Pandas
# tutorial).
- numexpr==2.6.9

# Optional: these libraries can be useful in the classification chapter,
# exercise 4.
- nltk==3.4.5
- graphviz
- imageio=2.6.1
- ipython=7.10.1
- ipywidgets=7.5.1
- joblib=0.14.0
- jupyter=1.0.0
- matplotlib=3.1.2
- nbdime=1.1.0
- nltk=3.4.4
- numexpr=2.7.0
- numpy=1.17.3
- pandas=0.25.3
- pillow=6.2.1
- pip=19.3.1
- py-xgboost=0.90
- pydot=1.4.1
- pyopengl=3.1.3b2
- python=3.7
- python-graphviz
- requests=2.22.0
- scikit-image=0.16.2
- scikit-learn=0.22
- scipy=1.3.1
- tqdm=4.40.0
- tensorboard=1.15.0
- tensorflow=1.15.0 # or tensorflow-gpu if gpu
- tensorflow-base=1.15.0
- tensorflow-datasets=1.2.0
- tensorflow-estimator=1.15.1
- tensorflow-hub=0.7.0
- tensorflow-metadata=0.14.0
- tensorflow-probability=0.7
- wheel=0.33.6
- widgetsnbextension=3.5.1
- pip:
- urlextract==0.9

# Optional: tqdm displays nice progress bars, ipywidgets for tqdm's notebook support
- tqdm==4.31.1
- ipywidgets==7.4.2

# Optional: Some useful extensions to customize and configure jupyter notebooks
- jupyter_contrib_nbextensions
- jupyter_nbextensions_configurator

name: mlbook
- atari-py==0.2.6 # on Windows, use: pip install --no-index -f https://github.com/Kojoley/atari-py/releases atari_py
- gym==0.15.4
- opencv-python==4.1.2.30
- psutil==5.6.7
- pyglet==1.3.2
- tensorflow-serving-api==1.15.0 # or tensorflow-serving-api-gpu if gpu
- tf-agents==0.3.0rc0
- urlextract==0.13.0
- tensorflow-data-validation==0.15.0 # remove if on windows
- tensorflow-model-analysis==0.15.4 # remove if on windows
- tensorflow-transform==0.15.0 # remove if on windows
- tfx==0.15.0 # remove if on windows
#- pyvirtualdisplay # add if on headless server
@@ -1,82 +1,84 @@
# First make sure to update pip:
# $ sudo pip install --upgrade pip
#
# Then you probably want to work in a virtualenv (optional):
# $ sudo pip install --upgrade virtualenv
# Or if you prefer you can install virtualenv using your favorite packaging
# system. E.g., in Ubuntu:
# $ sudo apt-get update && sudo apt-get install virtualenv
# Then:
# $ cd $my_work_dir
# $ virtualenv my_env
# $ . my_env/bin/activate
#
# Next, optionally uncomment the OpenAI gym lines (see below).
# If you do, make sure to install the dependencies first.
# If you are interested in xgboost for high performance Gradient Boosting, you
# should uncomment the xgboost line (used in the ensemble learning notebook).
#
# Then install these requirements:
# $ pip install --upgrade -r requirements.txt
#
# Finally, start jupyter:
# $ jupyter notebook
#

# See the installation instructions at https://github.com/ageron/handson-ml

##### Core scientific packages
jupyter==1.0.0
matplotlib==3.0.3
numpy==1.16.2
pandas==0.24.1
scipy==1.2.1
matplotlib==3.1.2
numpy==1.17.3
pandas==0.25.3
scipy==1.3.1

# Efficient jobs (caching, parallelism, persistence)
joblib==0.14.0

# Easy http requests
requests==2.22.0

##### Machine Learning packages
scikit-learn==0.20.3
scikit-learn==0.22

# Optional: the XGBoost library is only used in the ensemble learning chapter.
xgboost==0.82

xgboost==0.90

##### 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 must install CUDA, cuDNN and more: see tensorflow.org for the detailed
# installation instructions.
tensorflow==1.13.1
#tensorflow-gpu==1.13.1
tensorflow==1.15.0
#tensorflow-gpu==1.15.0

tensorboard==1.15.0
tensorflow-estimator==1.15.1


# 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]==0.15.4
# If you only want to install the Atari dependency, uncomment this line instead:
#gym[atari]==0.10.9
#gym[atari]==0.15.4

# On Windows, install atari_py using:
# pip install --no-index -f https://github.com/Kojoley/atari-py/releases atari_py

##### Image manipulation
imageio==2.5.0
Pillow==6.2.0
scikit-image==0.14.2
imageio==2.6.1
Pillow==6.2.1
scikit-image==0.16.2
graphviz
pydot==1.4.1
opencv-python==4.1.2.30
pyglet==1.3.2

#pyvirtualdisplay # needed in chapter 16, if on a headless server (without screen, e.g., Colab or VM)

##### Extra packages (optional)

# Nice utility to diff Jupyter Notebooks.
#nbdime==1.0.5
nbdime==1.1.0

# May be useful with Pandas for complex "where" clauses (e.g., Pandas
# tutorial).
numexpr==2.6.9
numexpr==2.7.0

# Optional: these libraries can be useful in the classification chapter,
# exercise 4.
nltk==3.4.5
urlextract==0.9
nltk==3.4.4
urlextract==0.13.0

# Optional: tqdm displays nice progress bars, ipywidgets for tqdm's notebook support
tqdm==4.31.1
ipywidgets==7.4.2
tqdm==4.40.0
ipywidgets==7.5.1

# Other useful TensorFlow-related packages you may want
#tensorflow-data-validation==0.15.0 # remove if on windows
#tensorflow-datasets==1.2.0
#tensorflow-hub==0.7.0
#tensorflow-metadata==0.14.0
#tensorflow-model-analysis==0.15.4 # remove if on windows
#tensorflow-probability==0.7
#tensorflow-serving-api==1.15.0 # or tensorflow-serving-api-gpu if gpu
#tensorflow-transform==0.15.0 # remove if on windows
#tfx==0.15.0 # remove if on windows
#tf-agents==0.3.0rc0

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