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What is this?
A collection of Jupyter notebooks with example code and exercise solutions for the 3rd edition of the O'Reilly book 'Hands-on Machine Learning with Scikit-Learn, Keras and TensorFlow'.
A collection of Jupyter notebooks with example code and exercise solutions for the 3rd edition of the O'Reilly book 'Hands-on Machine Learning with Scikit-Learn, Keras and TensorFlow'.Is this a standalone course or does it require the book?It's a companion notebook repository for the book, but the notebooks themselves walk through ML and Deep Learning fundamentals with runnable code, so you can learn from them even without the book.
It's a companion notebook repository for the book, but the notebooks themselves walk through ML and Deep Learning fundamentals with runnable code, so you can learn from them even without the book.How do I run these notebooks?Easiest way is to open them in Google Colab with no install needed; alternatively install Anaconda/Miniconda and git, clone the repo, run 'conda env create -f environment.yml', activate the 'homl3' env, register the Jupyter kernel, then launch 'jupyter notebook'. A Docker image is also provided.
Easiest way is to open them in Google Colab with no install needed; alternatively install Anaconda/Miniconda and git, clone the repo, run 'conda env create -f environment.yml', activate the 'homl3' env, register the Jupyter kernel, then launch 'jupyter notebook'. A Docker image is also provided.Is Google Colab a permanent place to keep my work?No, Colab gives you a temporary environment that gets wiped after a while, so you need to download anything you want to keep.
No, Colab gives you a temporary environment that gets wiped after a while, so you need to download anything you want to keep.Which Python version should I use?Python 3.10 is recommended (what you get by following the install instructions), though any version 3.7 or above should also work.
Python 3.10 is recommended (what you get by following the install instructions), though any version 3.7 or above should also work.Where can I find older editions of this book's notebooks?The 2nd edition notebooks are in ageron/handson-ml2 and the 1st edition notebooks are in ageron/handson-ml.
The 2nd edition notebooks are in ageron/handson-ml2 and the 1st edition notebooks are in ageron/handson-ml.Can I just browse the notebooks without running any code?Yes, GitHub's built-in notebook viewer works, though it's slower, math equations don't always render correctly, and large notebooks sometimes fail to open.
Yes, GitHub's built-in notebook viewer works, though it's slower, math equations don't always render correctly, and large notebooks sometimes fail to open.I'm getting an SSL error on macOS, what do I do?Run the Install Certificates command bundled with your Python installation (e.g. '/Applications/Python 3.10/Install Certificates.command'), or install curl-ca-bundle via MacPorts if that's how you installed Python.
Run the Install Certificates command bundled with your Python installation (e.g. '/Applications/Python 3.10/Install Certificates.command'), or install curl-ca-bundle via MacPorts if that's how you installed Python.What are similar projects?handson-ml2, machine-learning-zoomcamp, d2l-en, DeepLearning, ailearning, handson-ml, deep-learning-with-python-notebooks, 100-Days-Of-ML-Code
handson-ml2, machine-learning-zoomcamp, d2l-en, DeepLearning, ailearning, handson-ml, deep-learning-with-python-notebooks, 100-Days-Of-ML-CodeWhich topics is it in?keras, scikit-learn, tensorflow, reinforcement-learning, neural-network, jupyter notebook, data-science, book, computer-vision, pytorch, learning, tutorial
keras, scikit-learn, tensorflow, reinforcement-learning, neural-network, jupyter notebook, data-science, book, computer-vision, pytorch, learning, tutorial