Keras Preprocessing Layers
Вставка
- Опубліковано 30 чер 2024
- Google Software Engineer Matthew Watson highlights Keras Preprocessing Layers’ ability to streamline model development workflows. Follow along as he builds an end-to-end model showing what you can do with these layers.
Chapters
0:00 - Introduction
1:18 - Identifying the problem
6:01 - What are Keras preprocessing layers
9:45 - Preprocessing layers that are offered
17:37 - Transforming inputs from strings to a numeric input
22:17 - Building a simple model
24:13 - Adding a new feature
27:40 - Better performance with tf.data
33:22 - Multi worker training
35:26 - Takeaways
Resources:
Matthew Watson Github → goo.gle/3wfFjGY
Preprocessing layers guide → goo.gle/36qE2SA
Text loading tutorial → goo.gle/3JyFCR2
Image loading tutorial → goo.gle/3IuJZew
Watch more ML Tech Talks → goo.gle/ml-tech-talks
Subscribe to TensorFlow → goo.gle/TensorFlow
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It could be helpful to explain how to build a preprocessing layer with different preprocessing for each feature.
That's amazingly cool! Thanks!
that's great explanation! thank you
This was what i was waiting for a long time before switching back to keras again ! I have been asking this question here and there all over the internet lol. Now here we go ! Thanks!
Could you give the link of the code and the presentation. Also is there a website where I can find these resources. Is there any I can get certified by TensorFlow that I know this library? I am a junior in university trying to learn machine learning
Hi tensorflow team,
I tried the examples, but
train_ds = tfds.load('imdb_reviews', split=['train'], as_supervised=True)
train_ds = train_ds.batch(8)
gives an error "' list' object has no attribute 'batch' ". Any idea why?
Looks like the object is a list of dataset instead of being a dataset.
Try: train_ds = train_ds[0]
i had the same issue , while trouble shooting i found that
split=['train'] was issue. Changed it to 'train' (without array) and it worked
How can I get these slides? Thanks.
Where can i find the slides for reference?
Can I use a normalization layer as an output layer ?
Hi tensorflow team , i want implant nn.parameter functionality with keras and tensorflow. Can you give some suggestions to how used keras and tensorflow as nn.parameter in my code.
I'd ask this on the TensorFlow Forum. It's much easier to get answers there.
Is it only the “adapt” function that isn’t good for large datasets or is it all preprocessing using keras layers? If the preprocessing layers aren’t supposed to be used for large datasets I have to wonder what’s the point??
Yes, it's only the adapt function
@@lgmuk thanks, that’s good. What’s the best way to still use the keras preprocessing layers while needing to transform in beam?
@@greedybuddha795 Maybe use TF Tranform. That's projected for bigger pipelines and infrastructure
Before making my comments I really want to stress that everything you've said in this video are valid and useful - but for someone who probably has had prior training and knowledge of the subject matter. The dialogue in your video is akin to a conversation between Google engineers working in a team developing some sort of API, all fully immersed in the context and possessing multifaceted knowledgeable about the problem and solution domains. Almost everyone in Tensorflow and Keras teams make those assumptions and quite frankly the usefulness of their tutorials end after the initial introduction. Try anther video without those assumption and for someone who may not be fully aware of everything to do with Tensorflow Libraries or Keras API exposing those libraries' functions. Then I'll be the first to subscribe.
This is totally the norm for any sort of technical documentation. It's written by experts, who no longer remember what neophytes do not know. The Keras and TF documentation is among the worst for assuming everyone is an expert already.
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