Closed lillythomas closed 1 year ago
Found 4 changed notebooks. Review the changes at https://gitnotebooks.com/developmentseed/tensorflow-eo-training-2/pull/6
cna > can
Tip: open the notebook in vscode, it should highlight spelling issues.
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Nice to have, an answer to the question above.
variable: loss value, changes with each epoch constant: fixed hyper parameters like batch size
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A "vector" is a "rank-1" tensor and contains something like a list of values > In ML, a "vector" is a "rank-1" tensor and contains a list of values
In mathematics vectors can have more than 1 dimension, but when it comes to ML, vectors typically refer to single dimensional arrays. I think we can omit the last sentence "A vector is characterized by having one axis." since this doesn't hold depending on who you're talking to.
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Word. I actually provide an answer a bit later on, discussing how trainable weights should be variables. But I like these suggestions too.
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can delete "and mostly out of scope for now", implied
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definition of rank happens after the term is introduced, can you shift where it is introduced below this or move these definitions up?
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I think we can leave out "It's also used in the making of data pipelines."
We don't introduce the concept of functional data pipes in this lesson so this might confuse learners
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can also remove data pipes here too. unless we introduce TF's concept of it with code.
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ok here I think is where we map tf.data.dataset to data pipes, should be data pipes for consistency.
can this introduction be moved up? and I think in that case, good to expand and define data pipes and include the references to datapipes.
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Reviewed and revised per all of the suggested changes. Merging now.
Relates to https://github.com/developmentseed/servir-amazonia-2-internal/issues/5
In this lesson, we go through: