96 lines
2.5 KiB
Plaintext
96 lines
2.5 KiB
Plaintext
# TensorFlow is much easier to install using Anaconda, especially
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# on Windows or when using a GPU. Please see the installation
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# instructions in INSTALL.md
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##### Core scientific packages
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jupyterlab~=3.2.0
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matplotlib~=3.4.3
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numpy~=1.19.5
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pandas~=1.3.3
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scipy~=1.7.1
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##### Machine Learning packages
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scikit-learn~=1.0.1
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# Optional: the XGBoost library is only used in chapter 6
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xgboost~=1.4.2
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# Optional: the transformers library is only using in chapter 15
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transformers~=4.11.3
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##### TensorFlow-related packages
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# If you have a TF-compatible GPU and you want to enable GPU support, then
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# replace tensorflow-serving-api with tensorflow-serving-api-gpu.
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# Your GPU must have CUDA Compute Capability 3.5 or higher support, and
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# you must install CUDA, cuDNN and more: see tensorflow.org for the detailed
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# installation instructions.
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tensorflow~=2.6.0
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# Optional: the TF Serving API library is just needed for chapter 18.
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tensorflow-serving-api~=2.6.0 # or tensorflow-serving-api-gpu if gpu
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tensorboard~=2.7.0
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tensorboard-plugin-profile~=2.5.0
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tensorflow-datasets~=4.4.0
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tensorflow-hub~=0.12.0
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tensorflow-probability~=0.14.1
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# Optional: only used in chapter 12.
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tfx~=1.3.0
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# Optional: only used in chapter 15.
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tensorflow-addons~=0.14.0
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##### Reinforcement Learning library (chapter 17)
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# There are a few dependencies you need to install first, check out:
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# https://github.com/openai/gym#installing-everything
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gym[Box2D,atari,accept-rom-license]~=0.21.0
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# WARNING: on Windows, installing Box2D this way requires:
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# * Swig: http://www.swig.org/download.html
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# * Microsoft C++ Build Tools: https://visualstudio.microsoft.com/visual-cpp-build-tools/
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# It's much easier to use Anaconda instead.
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tf-agents~=0.10.0
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##### Image manipulation
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Pillow~=8.4.0
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graphviz~=0.17
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opencv-python~=4.5.3.56
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pyglet~=1.5.21
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#pyvirtualdisplay # needed in chapter 17, if on a headless server
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# (i.e., without screen, e.g., Colab or VM)
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##### Additional utilities
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# Efficient jobs (caching, parallelism, persistence)
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joblib~=0.14.1
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# Easy http requests
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requests~=2.26.0
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# Nice utility to diff Jupyter Notebooks.
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nbdime~=3.1.0
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# May be useful with Pandas for complex "where" clauses (e.g., Pandas
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# tutorial).
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numexpr~=2.7.3
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# Optional: these libraries can be useful in the chapter 3, exercise 4.
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nltk~=3.6.5
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urlextract~=1.4.0
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# Optional: these libraries are only used in chapter 15
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ftfy~=6.0.3
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# Optional: tqdm displays nice progress bars, ipywidgets for tqdm's notebook support
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tqdm~=4.62.3
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ipywidgets~=7.6.5
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