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Victor Khaustov 2022-05-18 17:54:39 +09:00
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@ -2,11 +2,11 @@ Machine Learning Notebooks, 3rd edition
=================================
This project aims at teaching you the fundamentals of Machine Learning in
python. 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)](https://homl.info/er3):
python. It contains the example code and solutions to the exercises in the third edition of my O'Reilly book [Hands-on Machine Learning with Scikit-Learn, Keras and TensorFlow (3rd edition)](https://homl.info/er3):
<img src="https://images-na.ssl-images-amazon.com/images/I/51aqYc1QyrL._SX379_BO1,204,203,200_.jpg" title="book" width="150" />
**Note**: If you are looking for the second edition notebooks, check out [ageron/handson-ml2](https://github.com/ageron/handson-ml2). For the first edition, see check out [ageron/handson-ml](https://github.com/ageron/handson-ml).
**Note**: If you are looking for the second edition notebooks, check out [ageron/handson-ml2](https://github.com/ageron/handson-ml2). For the first edition, see [ageron/handson-ml](https://github.com/ageron/handson-ml).
## Quick Start
@ -34,7 +34,7 @@ Read the [Docker instructions](https://github.com/ageron/handson-ml3/tree/main/d
### Want to install this project on your own machine?
Start by installing [Anaconda](https://www.anaconda.com/distribution/) (or [Miniconda](https://docs.conda.io/en/latest/miniconda.html)), [git](https://git-scm.com/downloads), and if you have a TensorFlow-compatible GPU, install the [GPU driver](https://www.nvidia.com/Download/index.aspx), as well as the appropriate version of CUDA and cuDNN (see TensorFlow's documentation for more details).
Start by installing [Anaconda](https://www.anaconda.com/products/distribution) (or [Miniconda](https://docs.conda.io/en/latest/miniconda.html)), [git](https://git-scm.com/downloads), and if you have a TensorFlow-compatible GPU, install the [GPU driver](https://www.nvidia.com/Download/index.aspx), as well as the appropriate version of CUDA and cuDNN (see TensorFlow's documentation for more details).
Next, clone this project by opening a terminal and typing the following commands (do not type the first `$` signs on each line, they just indicate that these are terminal commands):