• 4 months ago
In this second part (more code focused), we'll jump into Spacy for exploiting this Neural Linguistic Processing tool for recognizing entities while manipulating its data.
Then we'll finally move to NetworkX for getting an overall visualization of all connections between each element found.

If you missed Part 1: https://youtu.be/Nmzu3tppIX8

⌛------------Timestamp-------------⌛
00:00 - Intro: where we left and what we'll see today
01:05 - Spacy: Creating our Pipeline
04:03 - Spacy: Implementing Tokenization and Pipelines
05:49 - A WordCloud of entities
10:10 - Data Manipulation: counting entities and combos
15:16 - NetworkX: how it works
16:24 - NetworkX: creating graphs and visualizing networks
23:28 - Creating Community clusters
26:58 - NetworkX: a last plot for labels and entities
31:56 - Ending

------------Link-------------
- Link GitHub files: https://github.com/beppedataworld/ChatGPT-Spacy-NetworkX
- Link Medium Article: https://medium.com/p/2b40d346d97e
- Spacy Pipelines: https://spacy.io/usage/processing-pipelines
- Spacy Trained Models & Pipelines: https://spacy.io/models
- Network X Official Documentation: https://networkx.org/documentation/latest/reference/introduction.html
- Pyvis Official Doc: https://pyvis.readthedocs.io/en/latest/
- NetworkX Louvain_community: https://networkx.org/documentation/stable/reference/algorithms/generated/networkx.algorithms.community.louvain.louvain_communities.html
- Community API: https://python-louvain.readthedocs.io/en/latest/

------------Music/Images/Video Credits-----------
- "Ambient Piano and Strings" by Good_B_Music: https://pixabay.com/it/music/bei-giochi-ambient-piano-and-strings-10711/
- Robotic/Skynet clip by JawadAliKhan : https://pixabay.com/it/videos/scanner-umano-ia-172156/

Category

📚
Learning

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