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Aurélien Geron 2023-11-14 18:09:29 +13:00
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60
environment.yml
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@ -4,42 +4,42 @@ channels:
- defaults - defaults
dependencies: dependencies:
- box2d-py=2.3 # used only in chapter 18, exercise 8 - box2d-py=2.3 # used only in chapter 18, exercise 8
- ffmpeg=5.1 # used only in the matplotlib tutorial to generate animations - ffmpeg=6.1 # used only in the matplotlib tutorial to generate animations
- graphviz # used only in chapter 6 for dot files - graphviz # used only in chapter 6 for dot files
- python-graphviz # used only in chapter 6 for dot files - python-graphviz # used only in chapter 6 for dot files
- ipython=8.5 # a powerful Python shell - ipython=8.17 # a powerful Python shell
- ipywidgets=8.0 # optionally used only in chapter 12 for tqdm in Jupyter - ipywidgets=8.1 # optionally used only in chapter 12 for tqdm in Jupyter
- joblib=1.1 # used only in chapter 2 to save/load Scikit-Learn models - joblib=1.3 # used only in chapter 2 to save/load Scikit-Learn models
- jupyterlab=3.4 # to edit and run Jupyter notebooks - jupyterlab=4.0 # to edit and run Jupyter notebooks
- matplotlib=3.5 # beautiful plots. See tutorial tools_matplotlib.ipynb - matplotlib=3.8 # beautiful plots. See tutorial tools_matplotlib.ipynb
- nbdime=3.1 # optional tool to diff Jupyter notebooks - nbdime=3.2 # optional tool to diff Jupyter notebooks
- nltk=3.6 # optionally used in chapter 3, exercise 4 - nltk=3.8 # optionally used in chapter 3, exercise 4
- numexpr=2.8 # used only in the Pandas tutorial for numerical expressions - numexpr=2.8 # used only in the Pandas tutorial for numerical expressions
- numpy=1.23 # Powerful n-dimensional arrays and numerical computing tools - numpy=1.26 # Powerful n-dimensional arrays and numerical computing tools
- pandas=1.4 # data analysis and manipulation tool - pandas=2.1 # data analysis and manipulation tool
- pillow=9.2 # image manipulation library, (used by matplotlib.image.imread) - pillow=10.1 # image manipulation library, (used by matplotlib.image.imread)
- pip # Python's package-management system - pip # Python's package-management system
- py-xgboost=1.6 # used only in chapter 6 for optimized Gradient Boosting - py-xgboost=1.7 # used only in chapter 6 for optimized Gradient Boosting
- pydot=1.4 # used only for in chapter 10 for tf.keras.utils.plot_model() - pydot=1.4 # used only for in chapter 10 for tf.keras.utils.plot_model()
- python=3.10 # your beloved programming language! :) - python=3.10 # your beloved programming language! :)
- requests=2.28 # used only in chapter 19 for REST API queries - requests=2.31 # used only in chapter 19 for REST API queries
- scikit-learn=1.1 # machine learning library - scikit-learn=1.3 # machine learning library
- scipy=1.9 # scientific/technical computing library - scipy=1.11 # scientific/technical computing library
- statsmodels=0.13 # used only in chapter 15 for time series analysis - statsmodels=0.14 # used only in chapter 15 for time series analysis
- tqdm=4.64 # used only in chapter 12 to display nice progress bars - tqdm=4.66 # used only in chapter 12 to display nice progress bars
- wheel # built-package format for pip - wheel # built-package format for pip
- widgetsnbextension=4.0 # interactive HTML widgets for Jupyter notebooks - widgetsnbextension=4.0 # interactive HTML widgets for Jupyter notebooks
- pip: - pip:
- keras-tuner~=1.1.3 # used in chapters 10 and 19 for hyperparameter tuning - keras-core # used in chapter 10
- tensorboard-plugin-profile~=2.8.0 # profiling plugin for TensorBoard - keras-tuner~=1.4.6 # used in chapters 10 and 19 for hyperparameter tuning
- tensorboard~=2.10.0 # TensorFlow's visualization toolkit - tensorboard-plugin-profile~=2.14.0 # profiling plugin for TensorBoard
- tensorflow-addons~=0.17.1 # used in chapters 11 & 16 (for AdamW & seq2seq) - tensorboard~=2.14.1 # TensorFlow's visualization toolkit
- tensorflow-datasets~=4.6.0 # datasets repository, ready to use - tensorflow-datasets~=4.9.3 # datasets repository, ready to use
- tensorflow-hub~=0.12.0 # trained ML models repository, ready to use - tensorflow-hub~=0.15.0 # trained ML models repository, ready to use
- tensorflow-serving-api~=2.10.0 # or tensorflow-serving-api-gpu if gpu - tensorflow-serving-api~=2.14.0 # or tensorflow-serving-api-gpu if gpu
- tensorflow~=2.10.0 # Deep Learning library - tensorflow~=2.14.0 # Deep Learning library
- transformers~=4.21.3 # Natural Language Processing lib for TF or PyTorch - transformers~=4.35.0 # Natural Language Processing lib for TF or PyTorch
- urlextract~=1.6.0 # optionally used in chapter 3, exercise 4 - urlextract~=1.8.0 # optionally used in chapter 3, exercise 4
- gym[classic_control,atari,accept-rom-license]~=0.26.1 # used only in ch18 - gym[classic_control,atari,accept-rom-license] # used only in ch18
- google-cloud-aiplatform~=1.17.0 # used only in chapter 19 - google-cloud-aiplatform~=1.36.2 # used only in chapter 19
- google-cloud-storage~=2.5.0 # used only in chapter 19 - google-cloud-storage~=2.13.0 # used only in chapter 19

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requirements.txt
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@ -4,20 +4,20 @@
##### Core scientific packages ##### Core scientific packages
jupyterlab~=3.4.6 jupyterlab~=4.0.8
matplotlib~=3.5.3 matplotlib~=3.8.1
numpy~=1.23.3 numpy~=1.26.2
pandas~=1.4.4 pandas~=2.1.3
scipy~=1.9.1 scipy~=1.11.3
##### Machine Learning packages ##### Machine Learning packages
scikit-learn~=1.1.2 scikit-learn~=1.3.2
# Optional: the XGBoost library is only used in chapter 7 # Optional: the XGBoost library is only used in chapter 7
xgboost~=1.6.2 xgboost~=2.0.2
# Optional: the transformers library is only used in chapter 16 # Optional: the transformers library is only used in chapter 16
transformers~=4.21.3 transformers~=4.35.0
##### TensorFlow-related packages ##### TensorFlow-related packages
@ -27,26 +27,24 @@ transformers~=4.21.3
# you must install CUDA, cuDNN and more: see tensorflow.org for the detailed # you must install CUDA, cuDNN and more: see tensorflow.org for the detailed
# installation instructions. # installation instructions.
tensorflow~=2.10.0 tensorflow~=2.14.0
keras-core
# Optional: the TF Serving API library is just needed for chapter 18. # Optional: the TF Serving API library is just needed for chapter 18.
tensorflow-serving-api~=2.10.0 # or tensorflow-serving-api-gpu if gpu tensorflow-serving-api~=2.14.0 # or tensorflow-serving-api-gpu if gpu
tensorboard~=2.10.0 tensorboard~=2.14.1
tensorboard-plugin-profile~=2.8.0 tensorboard-plugin-profile~=2.14.0
tensorflow-datasets~=4.6.0 tensorflow-datasets~=4.9.3
tensorflow-hub~=0.12.0 tensorflow-hub~=0.15.0
# Used in chapter 10 and 19 for hyperparameter tuning # Used in chapter 10 and 19 for hyperparameter tuning
keras-tuner~=1.1.3 keras-tuner~=1.4.6
# Optional: used in chapters 11 & 16 (for AdamW & seq2seq)
tensorflow-addons~=0.17.1
##### Reinforcement Learning library (chapter 18) ##### Reinforcement Learning library (chapter 18)
# There are a few dependencies you need to install first, check out: # There are a few dependencies you need to install first, check out:
# https://github.com/openai/gym#installing-everything # https://github.com/openai/gym#installing-everything
gym[Box2D,atari,accept-rom-license]~=0.26.1 gym[Box2D,atari,accept-rom-license]~=0.26.2
# WARNING: on Windows, installing Box2D this way requires: # WARNING: on Windows, installing Box2D this way requires:
# * Swig: http://www.swig.org/download.html # * Swig: http://www.swig.org/download.html
@ -55,39 +53,40 @@ gym[Box2D,atari,accept-rom-license]~=0.26.1
# It's much easier to use Anaconda instead. # It's much easier to use Anaconda instead.
##### Image manipulation ##### Image manipulation
Pillow~=9.2.0 Pillow~=10.1.0
graphviz~=0.20.1 graphviz~=0.20.1
##### Google Cloud Platform - used only in chapter 19 ##### Google Cloud Platform - used only in chapter 19
google-cloud-aiplatform~=1.17.0 google-cloud-aiplatform~=1.36.2
google-cloud-storage~=2.5.0 google-cloud-storage~=2.13.0
##### Additional utilities ##### Additional utilities
# Efficient jobs (caching, parallelism, persistence) # Efficient jobs (caching, parallelism, persistence)
joblib~=1.1.0 joblib~=1.3.2
# Easy http requests # Easy http requests
requests~=2.28.1 requests~=2.31.0
# Nice utility to diff Jupyter Notebooks. # Nice utility to diff Jupyter Notebooks.
nbdime~=3.1.1 nbdime~=3.2.1
# May be useful with Pandas for complex "where" clauses (e.g., Pandas # May be useful with Pandas for complex "where" clauses (e.g., Pandas
# tutorial). # tutorial).
numexpr~=2.8.3 numexpr~=2.8.7
# Optional: these libraries can be useful in chapter 3, exercise 4. # Optional: these libraries can be useful in chapter 3, exercise 4.
nltk~=3.7 nltk~=3.8.1
urlextract~=1.6.0 urlextract~=1.8.0
# Optional: tqdm displays nice progress bars, ipywidgets for tqdm's notebook # Optional: tqdm displays nice progress bars, ipywidgets for tqdm's notebook
# support # support
tqdm~=4.64.1 tqdm~=4.66.1
ipywidgets~=8.0.2 ipywidgets~=8.1.1
# Optional: pydot is only used in chapter 10 for tf.keras.utils.plot_model() # Optional: pydot is only used in chapter 10 for tf.keras.utils.plot_model()
pydot~=1.4.2 pydot~=1.4.2
# Optional: statsmodels is only used in chapter 15 for time series analysis # Optional: statsmodels is only used in chapter 15 for time series analysis
statsmodels~=0.13.2 statsmodels~=0.14.0