Machine learning is becoming an important tool in many industries and fields of science. But ML research and product development present several challenges that, if not addressed, can steer your project in the wrong direction. By Ben Dickson.
Here are some takeaways from the article:
- Pay extra attention to data
- Know your models (as well as those of others)
- Know the final goal and its requirements
- Know what to measure and report
- Applied machine learning
When it comes to data, machine learning engineers must consider an extra set of considerations before integrating them into products. Some include data privacy and security, user consent, and regulatory constraints. Many a company has fallen into trouble for mining user data without their consent. Nice one!
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