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Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and MLOps
Paperback
Published October 28, 2020
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May 28, 2022
This is one of my favorite books of data science. Super practical! Highly recommended for ML data scientists and ML engineers. Lak is a great tutor. His books are very well written with code provided.
There are 30 patterns in this book, which describes problems, solutions, as well as trade-offs and alternatives. Those patterns cover various problems from data preprocessing to ML Ops. All patterns have sample code from TensorFlow and Keras, or BigQuery, which you can download from the GitHub GCP repository. The focus is not on "how to realize" the pattern, but on "why it works", so it is also a useful book for those who usually use other machine learning frameworks such as PyTorch.
There are 30 patterns in this book, which describes problems, solutions, as well as trade-offs and alternatives. Those patterns cover various problems from data preprocessing to ML Ops. All patterns have sample code from TensorFlow and Keras, or BigQuery, which you can download from the GitHub GCP repository. The focus is not on "how to realize" the pattern, but on "why it works", so it is also a useful book for those who usually use other machine learning frameworks such as PyTorch.
Displaying 1 of 1 review