Update to Python 3.8
Aurélien Geron
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@ -3,52 +3,51 @@ channels:
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- conda-forge
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- defaults
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dependencies:
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- atari_py=0.2.6 # used only in chapter 17
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- box2d-py=2.3 # used only in chapter 17
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- ftfy=6.0 # used only in chapter 15 by the transformers library
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- graphviz # used only in chapter 5 for dot files
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- gym=0.19 # used only in chapter 17
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- ipython=7.28 # a powerful Python shell
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- ipywidgets=7.6 # optionally used only in chapter 11 for tqdm in Jupyter
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- joblib=0.14 # used only in chapter 2 to save/load Scikit-Learn models
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- jupyter=1.0 # to edit and run Jupyter notebooks
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- matplotlib=3.4 # beautiful plots. See tutorial tools_matplotlib.ipynb
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- nbdime=3.1 # optional tool to diff Jupyter notebooks
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- nltk=3.6 # optionally used in chapter 3, exercise 4
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- numexpr=2.7 # used only in the Pandas tutorial for numerical expressions
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- numpy=1.19 # Powerful n-dimensional arrays and numerical computing tools
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- opencv=4.5 # used only in chapter 17 by TF Agents for image preprocessing
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- pandas=1.3 # data analysis and manipulation tool
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- pillow=8.3 # image manipulation library, (used by matplotlib.image.imread)
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- pip # Python's package-management system
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- py-xgboost=1.4 # used only in chapter 6 for optimized Gradient Boosting
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- pyglet=1.5 # used only in chapter 17 to render environments
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- pyopengl=3.1 # used only in chapter 17 to render environments
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- python=3.7 # Python! Not using latest version as some libs lack support
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- python-graphviz # used only in chapter 5 for dot files
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- pyvirtualdisplay=2.2 # used only in chapter 17 if on headless server
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- requests=2.26 # used only in chapter 18 for REST API queries
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- scikit-learn=1.0 # machine learning library
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- scipy=1.7 # scientific/technical computing library
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- tqdm=4.62 # a progress bar library
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- wheel # built-package format for pip
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- widgetsnbextension=3.5 # interactive HTML widgets for Jupyter notebooks
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- atari_py=0.2.6 # used only in chapter 17
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- box2d-py=2.3 # used only in chapter 17
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- ftfy=6.0 # used only in chapter 15 by the transformers library
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- graphviz # used only in chapter 5 for dot files
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- gym=0.19 # used only in chapter 17
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- ipython=7.28 # a powerful Python shell
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- ipywidgets=7.6 # optionally used only in chapter 11 for tqdm in Jupyter
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- joblib=0.14 # used only in chapter 2 to save/load Scikit-Learn models
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- jupyterlab=3.2 # to edit and run Jupyter notebooks
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- matplotlib=3.4 # beautiful plots. See tutorial tools_matplotlib.ipynb
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- nbdime=3.1 # optional tool to diff Jupyter notebooks
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- nltk=3.6 # optionally used in chapter 3, exercise 4
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- numexpr=2.7 # used only in the Pandas tutorial for numerical expressions
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- numpy=1.19 # Powerful n-dimensional arrays and numerical computing tools
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- opencv=4.5 # used only in chapter 17 by TF Agents for image preprocessing
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- pandas=1.3 # data analysis and manipulation tool
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- pillow=8.3 # image manipulation library, (used by matplotlib.image.imread)
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- pip # Python's package-management system
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- py-xgboost=1.4 # used only in chapter 6 for optimized Gradient Boosting
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- pyglet=1.5 # used only in chapter 17 to render environments
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- pyopengl=3.1 # used only in chapter 17 to render environments
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- python=3.8 # Python! Not using latest version as some libs lack support
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- python-graphviz # used only in chapter 5 for dot files
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- pyvirtualdisplay=2.2 # used only in chapter 17 if on headless server
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- requests=2.26 # used only in chapter 18 for REST API queries
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- scikit-learn=1.0 # machine learning library
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- scipy=1.7 # scientific/technical computing library
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- tqdm=4.62 # a progress bar library
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- wheel # built-package format for pip
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- widgetsnbextension=3.5 # interactive HTML widgets for Jupyter notebooks
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- pip:
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- tensorboard-plugin-profile==2.5.0 # profiling plugin for TensorBoard
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- tensorboard==2.6.0 # TensorFlow's visualization toolkit
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- tensorflow-addons==0.14.0 # used only in chapter 15 for a seq2seq impl.
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- tensorflow-datasets==4.4.0 # datasets repository, ready to use
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- tensorflow-hub==0.12.0 # trained ML models repository, ready to use
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- tensorflow-probability==0.14.1 # Optional. Probability/Stats lib.
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- tensorflow-serving-api==2.6.0 # or tensorflow-serving-api-gpu if gpu
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- tensorflow==2.6.0 # Deep Learning library
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- tf-agents==0.10.0 # Reinforcement Learning lib based on TensorFlow
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- tfx==1.3.0 # platform to deploy production ML pipelines
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- transformers==4.11.3 # Natural Language Processing lib for TF or PyTorch
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- urlextract==1.4.0 # optionally used in chapter 3, exercise 4
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- tensorboard-plugin-profile~=2.5.0 # profiling plugin for TensorBoard
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- tensorboard~=2.7.0 # TensorFlow's visualization toolkit
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- tensorflow-addons~=0.14.0 # used only in chapter 15 for a seq2seq impl.
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- tensorflow-datasets~=4.4.0 # datasets repository, ready to use
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- tensorflow-hub~=0.12.0 # trained ML models repository, ready to use
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- tensorflow-probability~=0.14.1 # Optional. Probability/Stats lib.
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- tensorflow-serving-api~=2.6.0 # or tensorflow-serving-api-gpu if gpu
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- tensorflow~=2.6.0 # Deep Learning library
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- tf-agents~=0.10.0 # Reinforcement Learning lib based on TensorFlow
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- tfx~=1.3.0 # platform to deploy production ML pipelines
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- transformers~=4.11.3 # Natural Language Processing lib for TF or PyTorch
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- urlextract~=1.4.0 # optionally used in chapter 3, exercise 4
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- attrs=20.3
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- click=7.1
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- packaging=20.9
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- six=1.15
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- typing-extensions=3.7
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@ -4,20 +4,20 @@
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##### Core scientific packages
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jupyter==1.0.0
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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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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
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scikit-learn~=1.0
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# Optional: the XGBoost library is only used in chapter 7
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xgboost==1.4.2
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xgboost~=1.4.2
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# Optional: the transformers library is only using in chapter 16
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transformers==4.11.3
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transformers~=4.11.3
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##### TensorFlow-related packages
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@ -27,70 +27,70 @@ transformers==4.11.3
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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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tensorflow~=2.6.0
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# Optional: the TF Serving API library is just needed for chapter 19.
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tensorflow-serving-api==2.6.0 # or tensorflow-serving-api-gpu if gpu
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tensorflow-serving-api~=2.6.0 # or tensorflow-serving-api-gpu if gpu
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tensorboard==2.6.0
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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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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 13.
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# Optional: only used in chapter 12.
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# NOT AVAILABLE ON WINDOWS
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tfx==1.3.0
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tfx~=1.3.0
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# Optional: only used in chapter 16.
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# Optional: only used in chapter 15.
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# NOT AVAILABLE ON WINDOWS
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tensorflow-addons==0.14.0
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tensorflow-addons~=0.14.0
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##### Reinforcement Learning library (chapter 18)
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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]==0.21.0
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gym[Box2D]~=0.21.0
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atari-py==0.2.5
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# On Windows, install atari_py using:
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# pip install --no-index -f https://github.com/Kojoley/atari-py/releases atari_py
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tf-agents==0.10.0
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tf-agents~=0.10.0
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##### Image manipulation
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Pillow==8.3.2
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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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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 16, if on a headless server
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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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joblib~=0.14.1
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# Easy http requests
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requests==2.26.0
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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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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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numexpr~=2.7.3
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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==3.6.3
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urlextract==1.4.0
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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 16
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ftfy==6.0.3
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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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tqdm~=4.62.3
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ipywidgets~=7.6.5
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