July 2018
Beginner to intermediate
406 pages
9h 55m
English
book
Building Machine Learning Systems with Python - Third Edition
by Luis Pedro Coelho, Willi Richert, Matthieu Brucher
Content preview from Building Machine Learning Systems with Python - Third Edition
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All that was left out
We did not cover every machine learning package available for Python. Given the limited space, we chose to focus on scikit-learn. However, there are other options and we list a few of them here:
- pandas (https://pandas.pydata.org) – If you decide to fall in love with just one Python package in your whole life, choose this one! It provides a convenience layer on top of NumPy and speeds up common tasks, such as interactive data preprocessing, tremendously.
- Of course, all the other exciting deep learning toolkits, such as CNTK (http://cntk.ai), PyTorch (https://pytorch.org/), MXNet (https://mxnet.apache.org/), Chainer (https://chainer.org/), DSSTNE (https://github.com/amzn/amazon-dsstne), or DyNet (https://github.com/clab/dynet ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.