Build an AI/NLP TV Series Analysis System with Hugging Face, Chatbots, Spacy, Gradio, and Python

In this video, you’ll learn how to analyze your favorite TV series with AI, LLMs, and NLP. You’ll start by gathering and scraping data from the internet using Scrapy. Then you’ll understand what Neural networks are and how they evolved to be those big LLMs. We will then shift to implementing our first LLM to get the main themes of the series using Hugging Face and Transformers. After that, we will Create a character Network that shows how big each character is and plot how strong the relationship between the characters is. This will be Spacy’s NER model, Network X, and Pyviz. The Third model will be the most common NLP task out there which is training your text classifier on a custom dataset. This will utilize Hugging Face and Transformers because it’s the best way to reach state-of-the-art results. Lastly, we will build our chatbot to imitate our favorite characters so that we can have a full conversation with them.


📚 In this video you will learn how to:
1. Gather and scrape data from the internet using Scrapy
2. Create a zero shot classifier with Hugging Face and Transformers
3. Extract Named entities from test with Spacy
4. Train your own Text classifier on a custom dataset
5. Build a Chat bot to imitate your favorite character.

Github Link: https://github.com/abdullahtarek

🛢 Datasets:
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dataset_1: https://subtitlist.com/subs/naruto-se...
dataset_2: https://www.kaggle.com/datasets/leonz...
dataset_3: https://naruto.fandom.com/wiki/Specia...


🔑 TIMESTAMPS
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0:00 - Introduction
1:20 - Gathering your Dataset
44:55 - NLP and Transformers Intro
1:08:24 - Theme Classification
2:35:55 - Character Network
3:31:20 - Text Classifier
4:49:15 - Character Chat Bot