#9 PyTorch Book Thread: Sunday 23rd Oct 8 AM PT

Note: This is a wiki, please edit it & add resources!

:tv: YouTube Link: PyTorch Book Reading - 9. Creating an End to End tumor classifier & Deploying to Production. - YouTube

Hey again, everybody!

I’m quite sad about hosting the last call, this has been quite the journey for me!

In this week, we’ll bring all the pieces together for an end to end pipeline and learn of various deployment options

:link: Link to sign up

:books: Resources:


When will I see more homework being turned in? :cry:

Q: What will an end to end pipeline look like?

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  1. prepare the data
  2. extract the nodules with segmentation
  3. feed the suspicious nodules to the final classifier
  1. Preparing the dataset
  2. Image Segmentation
  3. Nodule Determination
  4. Malignancy Determination
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Data Prep: DataSet, EDA, to confirm that Dataset is working well.
Training Pipeline: Run through sample batch
Evaluation Pipeline

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Yes. That makes sense. Didn’t want to miss the ending and stay connected.

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Even though I have only attended a few sessions, I loved the sessions. And I am excited to learn more and complete the book. You are an amazing host, Sanyam!

Please leave a like if you’d like to contribute to fast-ml coursework


Thank you @bhutanisanyam1 for an amazing 10 weeks of PyTorch! Eagerly awaiting the next study group (and many more after that one :smiley:) to learn with the community.

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