📖➡️🔢 From 0 to AI: How Language Representation Began? (One-Hot, BoW, TF-IDF) 🧠💡[Part 1/6]

How did AI start understanding human language? 🤯 In this video, we take a deep dive into the early methods of text representation: One-Hot Encoding, Bag of Words (BoW), and TF-IDF. These simple yet powerful techniques laid the foundation for modern Natural Language Processing (NLP) and AI.

🚀 What you’ll learn:
✅ How text is converted into numerical form 📊
✅ The limitations of early NLP models 🏛️
✅ Why these methods were essential for the AI revolution 🔥

00:00 Introduction
00:28 First methods: One-Hot Encoding, Bag of Words, TF-IDF
01:14 One-Hot Encoding presentation
02:35 Advantages and limitations of One-Hot Encoding
03:00 Bag of Words presentation
04:08 Advantages and limitations of Bag of Words
05:30 Term Frequency Inverse Document Frequency presentation
07:00 Advantages and limitations of Term Frequency Inverse Document Frequency presentation
07:55 Conclusion

How did AI start understanding human language? 🤯 In this video, we take a deep dive into the early methods of text representation: One-Hot Encoding, Bag of Words (BoW), and TF-IDF. These simple yet powerful techniques laid the foundation for modern Natural Language Processing (NLP) and AI.

🚀 What you’ll learn:
✅ How text is converted into numerical form 📊
✅ The limitations of early NLP models 🏛️
✅ Why these methods were essential for the AI revolution 🔥

Stay tuned for the next episode, where we explore the rise of Word2Vec, FastText, and Attention!

🔔 Don’t forget to LIKE, COMMENT, and SUBSCRIBE for more AI and NLP insights!

#AI #NLP #MachineLearning #DeepLearning #ArtificialIntelligence #OneHotEncoding #BagOfWords #TFIDF

Видео 📖➡️🔢 From 0 to AI: How Language Representation Began? (One-Hot, BoW, TF-IDF) 🧠💡[Part 1/6] канала Daniel Jora | AI Learner