GitHub - hoohawk/Roadmap-To-Learn-Generative-AI-In-2024
Prerequisites
1. Python Programming Language -1 Month
Python:

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Complete Python Playlist In English: 
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Complete Python Playlist In Hindi: 
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Flask Playlist: 
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Fast API Tutorials 
2. Basic Machine Learning Natural Language Processing (Day 1 - Day 5) 
- Why NLP?
- One hot Encoding, Bag Of Words,
- TFIDF
- Word2vec,AvgWord2vec
3. Basic Deep Learning Concepts (Day 1- Day 5) 
- ANN - Working Of MultiLayered Neural Network
- Forward Propogation, Backward Propogation
- Activation Functions, Loss Functions
- Optimizers
4. Advanced NLP Concepts (Day 6 - Last Video) 
- RNN, LSTM RNN
- GRU RNN
- Bidirection LSTM RNN
- Encoder Decoder, Attention is all you need ,Seq to Seq
- Transformers
5. Starting the Journey Towards Generative AI (GPT4,Mistral 7B, LLAMA, Hugging Face Open Source LLM Models,Google Palm Model)

- OpenAI


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Langchain Tutorials With Projects

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Chainlit 
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Google Gemini 
5. Vector Databases And Vector Stores
- ChromaDB
- FAISS vector database, which makes use of the Facebook AI Similarity Search (FAISS) library
- LanceDB vector database based on the Lance data format
- Cassandra DB For storing Vectors
6. Deployment Of LLM Projects
- AWS
- Azure
- LangSmith
- LangServe
- HuggingFace Spaces
iNeuron Free Community Generative Ai Series 
