Skip to content

Latest commit

 

History

History
71 lines (43 loc) · 3.48 KB

File metadata and controls

71 lines (43 loc) · 3.48 KB

Roadmap To Learn Generative AI In 2024

Prerequisites

1. Python Programming Language -1 Month

Python:

python-logo-master-v3-TM-flattened

  1. Complete Python Playlist In English: YouTube

  2. Complete Python Playlist In Hindi: YouTube

  3. Flask Playlist: YouTube

  4. Fast API Tutorials YouTube

2. Basic Machine Learning Natural Language Processing (Day 1 - Day 5) YouTube

  1. Why NLP?
  2. One hot Encoding, Bag Of Words,
  3. TFIDF
  4. Word2vec,AvgWord2vec

3. Basic Deep Learning Concepts (Day 1- Day 5) YouTube

  1. ANN - Working Of MultiLayered Neural Network
  2. Forward Propogation, Backward Propogation
  3. Activation Functions, Loss Functions
  4. Optimizers

4. Advanced NLP Concepts (Day 6 - Last Video) YouTube

  1. RNN, LSTM RNN
  2. GRU RNN
  3. Bidirection LSTM RNN
  4. Encoder Decoder, Attention is all you need ,Seq to Seq
  5. Transformers

5. Starting the Journey Towards Generative AI (GPT4,Mistral 7B, LLAMA, Hugging Face Open Source LLM Models,Google Palm Model)

image

  1. OpenAI YouTube YouTube

image

  1. Langchain Tutorials With Projects YouTube YouTube

  2. Chainlit YouTube

  3. Google Gemini YouTube

5. Vector Databases And Vector Stores

  1. ChromaDB
  2. FAISS vector database, which makes use of the Facebook AI Similarity Search (FAISS) library
  3. LanceDB vector database based on the Lance data format
  4. Cassandra DB For storing Vectors

6. Deployment Of LLM Projects

  1. AWS
  2. Azure
  3. LangSmith
  4. LangServe
  5. HuggingFace Spaces