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Multi-Dataframe Agents in Langchain
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Classroom Contents
Comprehensive Guide to Generative AI Development and Implementation
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- 1 Course Introduction
- 2 Introduction of the Instructor
- 3 Introduction to Generative AI
- 4 End to end Generative AI Pipeline
- 5 Data Preprocessing & cleaning
- 6 Data representation & vectorization for the model training
- 7 Text Classification Practical
- 8 Introduction to Large Language Models & its architecture
- 9 In depth intuition of Transformer-Attention all your need Paper
- 10 How ChatGPT is trained
- 11 Introduction of Hugging Face
- 12 Hands-On Hugging Face - Transformers, HF Pipeline, Datasets, LLMs
- 13 Data processing,Tokenizing and Feature Extraction with hugging face
- 14 Fine-tuning using a pretrain models
- 15 Hugging face API key generation
- 16 Project: Text summarization with hugging face
- 17 Project: Text to Image generation with LLM with hugging face
- 18 Project: Text to speech generation with LLM with hugging face
- 19 Introduction to OpenAI
- 20 How to generate OpenAI API key?
- 21 Local Environment Setup
- 22 Hands on OpenAI - ChatCompletion API and Completion API
- 23 Function Calling in OpenAI
- 24 Project: Telegram bot using OpenAI
- 25 Project: Finetuning of GPT-3 model for text classification
- 26 Project: Audio Transcript Translation with Whishper
- 27 Project: Image genration with DALL-E
- 28 Mastering Prompt Engineering
- 29 The Complete Introduction to Vector Databases
- 30 Mastering Vector Databases with ChromaDB
- 31 Mastering Vector Databases with Pinecone
- 32 Mastering Vector Databases with Weaviate
- 33 Introduction & Installation and setup of langchain
- 34 Prompt Templates in Langchain
- 35 Chains in Langchain
- 36 Langchain Agents and Tools
- 37 Memory in Langchain
- 38 Documents Loader in Langchain
- 39 Multi-Dataframe Agents in Langchain
- 40 How to use Hugging face Open Source LLM with Langchain
- 41 Project: Interview Questions Creator Application
- 42 Project: Custom Website Chatbot
- 43 Introduction to Open Source LLMs - Llama
- 44 How to use open source llms with Langchain
- 45 Custom Website Chatbot using Open source LLMs
- 46 Open Source LLMs - Falcon
- 47 Introduction & Importance of RAG
- 48 RAG Practical demo
- 49 RAG Vs Fine-tuning
- 50 Build a Q&A App with RAG using Gemini Pro and Langchain
- 51 What is Fine Tuning? Parameter Efficient Fine-Tuning - LoRA & QLoRA
- 52 Fine-Tuning Meta Llama 2 on Custom Data
- 53 Introduction to LlamaIndex & end to end Demo
- 54 Open Source Mistral LLM with LlamaIndex
- 55 Project: Financial Stock Analysis using LlamaIndex
- 56 Project: End to End Medical Chatbot with LLM, Pinecone, LangChain
- 57 Project: End to End Source Code Analysis with LangChain, LLM and ChromaDB
- 58 Project: Implementing Zomato chatbot with Chainlit
- 59 How to Deploy Generative AI Application as CICD on AWS
- 60 Introduction to LLMOps & Why we need it?
- 61 Generative AI with Google Cloud Vertex AI a LLMOps Platform
- 62 Vertex AI Hands-On on Google Cloud
- 63 Vertex AI Local Setup - Run Gemini Pro on Local Machine
- 64 RAG on Vertex AI with Vector Search and Gemini Pro
- 65 LLM powered application on Vertex AI
- 66 Fine-tuning Foundation Model on VertexAI
- 67 Introduction to AWS Bedrock
- 68 End to End RAG Project using AWS Bedrock
