handson-ml/environment.yml

name: homl3
channels:
  - conda-forge
  - defaults
dependencies:
  - atari_py=0.2.6 # used only in chapter 17
  - box2d-py=2.3 # used only in chapter 17
  - ftfy=6.0 # used only in chapter 15 by the transformers library
  - graphviz # used only in chapter 5 for dot files
  - gym=0.19 # used only in chapter 17
  - ipython=7.28 # a powerful Python shell
  - ipywidgets=7.6 # optionally used only in chapter 11 for tqdm in Jupyter
  - joblib=0.14 # used only in chapter 2 to save/load Scikit-Learn models
  - jupyter=1.0 # to edit and run Jupyter notebooks
  - matplotlib=3.4 # beautiful plots. See tutorial tools_matplotlib.ipynb
  - nbdime=3.1 # optional tool to diff Jupyter notebooks
  - nltk=3.6 # optionally used in chapter 3, exercise 4
  - numexpr=2.7 # used only in the Pandas tutorial for numerical expressions
  - numpy=1.19 # Powerful n-dimensional arrays and numerical computing tools
  - opencv=4.5 # used only in chapter 17 by TF Agents for image preprocessing
  - pandas=1.3 # data analysis and manipulation tool
  - pillow=8.3 # image manipulation library, (used by matplotlib.image.imread)
  - pip # Python's package-management system
  - py-xgboost=1.4 # used only in chapter 6 for optimized Gradient Boosting
  - pyglet=1.5 # used only in chapter 17 to render environments
  - pyopengl=3.1 # used only in chapter 17 to render environments
  - python=3.7 # Python! Not using latest version as some libs lack support
  - python-graphviz # used only in chapter 5 for dot files
  - pyvirtualdisplay=2.2 # used only in chapter 17 if on headless server
  - requests=2.26 # used only in chapter 18 for REST API queries
  - scikit-learn=1.0 # machine learning library
  - scipy=1.7 # scientific/technical computing library
  - tqdm=4.62 # a progress bar library
  - wheel # built-package format for pip
  - widgetsnbextension=3.5 # interactive HTML widgets for Jupyter notebooks
  - pip:
    - tensorboard-plugin-profile==2.5.0 # profiling plugin for TensorBoard
    - tensorboard==2.6.0 # TensorFlow's visualization toolkit
    - tensorflow-addons==0.14.0 # used only in chapter 15 for a seq2seq impl.
    - tensorflow-datasets==4.4.0 # datasets repository, ready to use
    - tensorflow-hub==0.12.0 # trained ML models repository, ready to use
    - tensorflow-probability==0.14.1 # Optional. Probability/Stats lib.
    - tensorflow-serving-api==2.6.0 # or tensorflow-serving-api-gpu if gpu
    - tensorflow==2.6.0 # Deep Learning library
    - tf-agents==0.10.0 # Reinforcement Learning lib based on TensorFlow
    - tfx==1.3.0 # platform to deploy production ML pipelines
    - transformers==4.11.3 # Natural Language Processing lib for TF or PyTorch
    - urlextract==1.4.0 # optionally used in chapter 3, exercise 4
  - attrs=20.3
  - click=7.1
  - packaging=20.9
  - six=1.15
  - typing-extensions=3.7