Update requirements.txt to latest version of each library
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@ -26,17 +26,17 @@
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##### Core scientific packages
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jupyter==1.0.0
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matplotlib==2.2.2
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numpy==1.14.3
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pandas==0.22.0
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scipy==1.1.0
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matplotlib==3.0.2
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numpy==1.15.4
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pandas==0.23.4
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scipy==1.2.0
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##### Machine Learning packages
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scikit-learn==0.19.1
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scikit-learn==0.20.1
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# Optional: the XGBoost library is only used in the ensemble learning chapter.
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#xgboost==0.71
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xgboost==0.81
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##### Deep Learning packages
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@ -45,47 +45,43 @@ scikit-learn==0.19.1
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# you need a GPU card with CUDA Compute Capability 3.0 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==1.8.0
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#tensorflow-gpu==1.8.0
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# Forcing bleach to 1.5 to avoid version incompatibility when installing
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# TensorBoard.
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bleach==1.5.0
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Keras==2.1.6
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tensorflow==1.12.0
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#tensorflow-gpu==1.12.0
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tensorflow-hub==0.2.0
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tensorflow-probability==0.5.0
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# Optional: OpenAI gym is only needed for the Reinforcement Learning chapter.
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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[all]==0.10.5
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#gym[all]==0.10.9
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# If you only want to install the Atari dependency, uncomment this line instead:
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#gym[atari]==0.10.5
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#gym[atari]==0.10.9
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##### Image manipulation
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imageio==2.3.0
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Pillow==5.1.0
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scikit-image==0.13.1
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imageio==2.4.1
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Pillow==5.3.0
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scikit-image==0.14.1
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##### Extra packages (optional)
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# Nice utility to diff Jupyter Notebooks.
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nbdime==0.4.1
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nbdime==1.0.4
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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==2.6.5
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numexpr==2.6.8
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# Optional: these libraries can be useful in the classification chapter,
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# exercise 4.
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nltk==3.3
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nltk==3.4
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urlextract==0.8.3
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# Optional: this extension is handy to easily start/stop tensorboard
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# server(s) directly from Jupyter.
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jupyter-tensorboard==0.1.6
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jupyter-tensorboard==0.1.8
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# Optional: these are useful Jupyter extensions, in particular to display the
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# table of contents
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