#PYTHON JUPYTER NOTEBOOK .YML INSTALL#
Start by installing Anaconda (or Miniconda), git, and if you have a TensorFlow-compatible GPU, install the GPU driver, as well as the appropriate version of CUDA and cuDNN (see TensorFlow's documentation for more details). Want to install this project on your own machine? Want to run this project using a Docker image? 's notebook viewer also works but it's not ideal: it's slower, the math equations are not always displayed correctly, and large notebooks often fail to open. Just want to quickly look at some notebooks, without executing any code? WARNING: Please be aware that these services provide temporary environments: anything you do will be deleted after a while, so make sure you download any data you care about. Use any of the following services (I recommended Colab or Kaggle, since they offer free GPUs and TPUs). Quick Start Want to play with these notebooks online without having to install anything?
For the first edition, see check out ageron/handson-ml. Note: If you are looking for the second edition notebooks, check out ageron/handson-ml2.
#PYTHON JUPYTER NOTEBOOK .YML CODE#
It contains the example code and solutions to the exercises in the second edition of my O'Reilly book Hands-on Machine Learning with Scikit-Learn, Keras and TensorFlow (3rd edition):
This project aims at teaching you the fundamentals of Machine Learning in
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