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

##### Core scientific packages
jupyter==1.0.0
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==0.22

# Optional: the XGBoost library is only used in the ensemble learning chapter.
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==1.15.2
#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]==0.15.4
# If you only want to install the Atari dependency, uncomment this line instead:
#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==2.6.1
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==1.1.0

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

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

# Optional: tqdm displays nice progress bars, ipywidgets for tqdm's notebook support
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