By: Oliver Zeldin, Sameer Indarapu, Damien Lefortier, Zheng Chen, Sushma Bannur The Facebook Field Guide to Machine Learning is a six-part video series developed by the Facebook ads machine learning team. The series shares best real-world practices and provides practical tips about how to apply machine-learning capabilities to real-world problems. Machine learning and artificial intelligence are in the headlines everywhere today, and there are many resources to teach you about how the algorithms work and demonstrations of the latest cutting-edge research.
However, if you’re interested in using machine learning to enhance your product in the real world, it’s important to understand how the entire development process works. It’s not only what happens during the training of your models, but everything that comes before and after, and how each step can either set you up for success or doom you to fail.
The Facebook ads machine learning team has developed a series of videos to help engineers and new researchers learn to apply their machine learning skills to real-world problems. The series breaks down the machine learning process into six steps: 1. Problem definition
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