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Lecture 5 of 21
What is NLP
Course Content
0 / 21 completedSection 1: Fundamentals of RAG2 videos
What is RAG RAG Process
12m
Generative AI without RAG. Why RAG
11m
Section 2: Introduction1 videos
Introduction to course
33m
Section 3: Fundamental of NLP5 videos
Tokenization, Stemming and Lemmatization
10m
What is NLP
8mNow Playing
Evaluation of NLP
14m
POS , NER , Chunking, BoW, TF-IDF and Embedding
30m
Transformer Model
38m
Section 4: Environment setup2 videos
Create simple streamlit chatbot
20m
Setup VS code , Python, Neo4j, Streamlit, PIP packages
1h 8m
Section 5: Implement chatbot with Vector RAG2 videos
What is vector RAG
11m
Develop vector RAG with Groq API and Langchain
53m
Section 6: Implement RAG chatbot with Graph RAG4 videos
Vector RAG vs Graph RAG
10m
What is Graph RAG
17m
Implement Graph RAG chatbot to build and show graph with Neo4j
1h 14m
Implement hybrid search with Graph RAG and Neo4j
1h 30m
Section 7: Implement Self-Reflective RAG or Adaptive RAG2 videos
Understand adaptive or self-reflective flow
5m
Implement Self-reflective RAG chatbot with Langgraph
1h 30m
Section 8: Autogen RAG Agentic RAG (newly added)1 videos
Autogen RAG Agentic RAG
39m
Section 9: Cohere ranking RAG(newly added)1 videos
Flow of Ranking RAG and LangChain Python coding
1h 8m
Section 10: Source Code , Advance Use Cases and Conclusion1 videos
Use Cases and Conclusion
21m