Categorical Entity Embedding Using Python Tensorflow Keras | Deep Learning

Categorical entity embedding extracts the embedding layers of categorical variables from a neural network model, and uses numeric vectors to represent the properties of the categorical values. It is usually used on categorical variables with high cardinalities.
In this tutorial, Python TensorFlow Keras is used to create categorical entity embeddings of Airbnb neighbourhood data. We will talk about:
👉 How to do data processing for categorical entity embedding?
👉 How to build a neural network model with entity embedding?
👉 How to extract the categorical embedding layers?
👉 How to use categorical entity embedding in other machine learning models?
⏰ Timecodes ⏰
0:00 - Intro
0:50 - Step 1: Install and Import Libraries
1:26 - Step 2: Download And Read Airbnb Review Data
3:51 - Step 3: Data Processing
5:18 - Step 4: Train Test Split
6:11 - Step 5: Categorical Data Label Encoding
7:02 - Step 6: Categorical Entity Embedding Model
14:39 - Step 7: Model Performance
15:55 - Step 8: Extract Categorical Embeddings
16:22 - Step 9: Save Entity Embedding Results
16:40 - Step 10: Baseline Random Forest Model
17:01 - Step 11: Use Categorical Entity Embedding in Other Machine Learning Models
❤️ Blog post with code for this video: / categorical-entity-emb...
📒 Code Notebook: mailchi.mp/9527a98c00ac/l7eqd...
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[@grabngoinfo]

❤ Blog post with code for this video: medium.com/@AmyGrabNGoInfo/categorical-entity-embedding-using-python-tensorflow-keras-dac153cbffd2
📒 Code Notebook: mailchi.mp/9527a98c00ac/l7eqdvbi3y
🚛 GrabNGoInfo Machine Learning Tutorials Inventory: medium.com/grabngoinfo/grabngoinfo-machine-learning-tutorials-inventory-9b9d78ebdd67
🙏 Give me a tip to show your appreciation and help me keep providing free content: www.paypal.com/donate/?hosted_button_id=4PZAFYA8GU8JW
✅ Join Medium Membership: If you are not a Medium member and want to support me to keep providing free content (😄 Buy me a cup of coffee ☕), join Medium membership through this link: medium.com/@AmyGrabNGoInfo/membership
You will get full access to posts on Medium for $5 per month, and I will receive a portion of it. Thank you for your support!
🎞 Deep Learning playlist: czcams.com/play/PLVppujud2yJqk0VRts7ylIoIzfBkA_3WT.html
📺 Videos mentioned in the video
Google Colab Tutorial for Beginners: czcams.com/video/nN0N_ZT2XYg/video.html

[@user-up8do5xm7q]

Thank you very much!
For a very long time I have been looking for information about embedding categorical variables in boosting models, but I found almost nothing or the information was incomprehensible. Now I understand everything. Thank you!

[@DavidKoleckar]

this was simply awesome

[@ssg7920]

x = reshape()(x)
what does x on the right side mean ?? Help me with that please
Similar to your documentation emb_cat = Reshape(....)(emb_cat)
What does emb_cat after Reshape function on the right side mean ?

[@grabngoinfo]

Hi SSg, the x in reshape()(x) and emb_cat in Reshape(....)(emb_cat) are the object passed in the reshape(). You can see that emb_cat is Keras Tensor with 3 dimensions before reshaping, and it's a Keras Tensor with 2 dimensions after reshaping.

[@ssg7920]

@@grabngoinfo So is the variable an object class variable??

[@user-up8do5xm7q]

notebook link is no longer available😭

[@balyapmayanari]

colab.research.google.com/drive/13U4YRIdEu7SWS1ttiJPSrSayQHNbIaT_?usp=sharing