🚀 Roadmap to Learning Generative AI in 2024

Ready to dive into the world of Generative AI? Here’s a step-by-step guide to mastering the essentials. Let’s get started!

1. 🐍 Python Programming Language

• Start with Python fundamentals to build a strong foundation for AI.

2. 📚 Basics of Machine Learning & NLP

• Why NLP? Understand the importance and applications of Natural Language Processing.
• Encoding Techniques
• One-Hot Encoding
• Bag of Words
• TF-IDF (Term Frequency-Inverse Document Frequency)
• Word Embedding
• Word2Vec
• AvgWord2Vec

3. 💡 Core Deep Learning Concepts

• Artificial Neural Networks (ANN)
• Learn the workings of Multi-Layered Neural Networks.
• Propagations
• Forward Propagation
• Backward Propagation
• Key Functions
• Activation Functions
• Loss Functions
• Optimizers

4. 🔍 Advanced NLP Concepts

• Recurrent Neural Networks (RNN)
• LSTM (Long Short-Term Memory)
• GRU (Gated Recurrent Units)
• Bidirectional LSTM
• Sequence-to-Sequence Models
• Encoder-Decoder Architecture
• Attention Mechanism (e.g., “Attention is All You Need”)
• Transformers

5. 🌐 Learning LLM & Generative AI

• Models to Explore
• GPT-4
• Mistral 7B
• LLAMA
• Hugging Face Open-Source Models
• Google PaLM
• Key Platforms and Libraries
• OpenAI
• LangChain
• Chainlit
• Google Gemini

6. 🗄️ Vector Databases & Vector Stores

• Popular Databases
• ChromaDB
• FAISS (Facebook AI Similarity Search)
• LanceDB (based on Lance format)
• Cassandra DB
• Pinecone

7. 🚀 Deploying LLM Projects

• Top Deployment Tools
• AWS Bedrock
• Azure ML
• LangSmith
• LangServe
• Hugging Face Spaces

Stay committed, explore these resources, and enjoy the journey of mastering Generative AI! 🌟