Blockchain Implementation Challenges

Blockchain Implementation Challenges >> Introduction to Machine Learning in Production

More computational power available

Can function even if network connection is down

Less network bandwidth needed

Lower latency

Correct: Edge deployments are frequently constrained in computational power due to cost, size, and energy requirements of the hardware.

Either transcription is okay, but the inconsistency is problematic.

The first is grammatically incorrect and we should use the second transcription.

The second is grammatically incorrect and we should use the first transcription.

We should not be transcribing “Umm.” The correct transcription, which serves the user’s needs better, is just “Today’s weather.

Correct: That’s right! The labelling instructions should remove ambiguity such that every example is labelled consistently.

False

True

Correct: That’s right! The last step of the machine learning project lifecycle is monitoring and maintenance, which is necessary because your project’s use cases and data may change over time!

It is a linear process, in which we move step-by-step from scoping to deployment. (That’s why we call it a cycle. Bicycles are only good at going forward, not backward.)

It is an iterative process, where during a later stage we might go back to an earlier stage. (That’s why we call it a cycle–it’s a circular process.)

Correct: That’s right!

Blockchain Implementation Challenges >> Introduction to Machine Learning in Production

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