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Introduction to LangChain (2023 - deprecated)

Introduction

Introduction to the course (2:50)
Setting up your Jupyter Notebook (optional) (4:07)
Special offer

LangChain Basics

Introduction (0:45)
What is LangChain - OpenAI API Key - Installing the Python Packages (3:24)
OpenAI package (temporary fix) (3:00)
LLMs (1:57)
Chains (2:58)
Prompt Templates (5:09)
Output parsers (3:25)
Simple Sequence (3:26)
Outro (0:14)

Loading and Summarizing Data

Introduction (0:35)
Loading Data (9:20)
Summary strategies (2:00)
Summarization examples (10:33)
Outro (0:17)

Prompt Engineering Fundamentals

Introduction (1:27)
Elements of a Prompt (1:38)
Few-Shot Learning (3:09)
Memetic Proxy (1:54)
Chain of Thought (5:17)
Self-Consistency (3:01)
Inception (2:10)
Self-Ask (4:20)
ReAct (4:29)
Plan and Execute (5:20)
Outro (0:18)

Vector Database Basics

Introduction (0:47)
Why Vector Databases? (2:00)
Similarity Metrics (2:48)
Why do we need Indexing? (0:55)
Product Quantization (1:58)
Locality Sensitive-Hashing (1:30)
Navigable Small World (2:05)
Hierarchical Navigable Small World (2:09)
Maximum Marginal Relevance (1:18)
Outro (1:00)

Retrieval Augmented Generation

Introduction (0:53)
Indexing data (8:09)
Loading data into a vector database (3:12)
Providing sources (4:44)
Indexing a website (6:03)
Indexing a GitHub repository (6:29)
The Stuff Strategy (4:21)
The Map-Reduce Strategy (4:13)
The Refine strategy (4:53)
The Map-Rerank strategy (5:28)
Outro (0:28)

RAG Optimization and Multimodal RAG

Introduction (0:47)
Multi-Vector Retriever (13:01)
Hypothetical Queries (7:45)
Parsing a Multimodal Document (6:01)
Summarizing the Data (2:45)
Describing Images with LlaVA (11:21)
Index the Data into a Database (8:55)
Finalizing the RAG Pipeline (2:15)
Outro (0:31)

Augmenting LLMs with a Graph Database

Introduction (1:03)
What is a Knowledge Base (2:02)
Getting the Data (2:06)
Create the Graph Representation (7:28)
Augmenting LLMs with a Knowledge Base (3:13)
Using the Diffbot Graph Transformer (3:43)
Creating a Local Graph Database (2:16)
Augmenting an LLM with the Graph Database (5:10)
Outro (0:39)

Augmenting LLMs with tools

Introduction (0:45)
What is an Agent? (0:57)
Agent Example (10:38)
Dissecting the Iterative Process (7:12)
The Different Tools (1:19)
Building Custom Tools (7:53)
Outro (0:28)

How to Build a Smart Voice Assistant

Introduction (2:13)
What are we building (1:00)
Setting up the Project (2:26)
From Speech to Text (5:14)
From Text to Speech (2:37)
Building a Conversational Agent (3:59)
Augmenting the Agent with Tools (7:05)
Outro (0:20)

How to Automate Writing Novels

Introduction (0:57)
Formalizing the Book Writing Process (2:33)
Setting up the Project (3:05)
The Main Character (6:42)
The Title (5:53)
The Plot (5:19)
The Chapters List (8:12)
The Chapters' Plots (14:32)
The Events List (12:08)
Writing the Book (9:20)
Writing to File (4:10)
Reading the Book (0:49)
The code from this lesson
Outro (0:21)

How to Automate Writing Software

Introduction (0:49)
The Strategy (2:07)
Setting up the Project (1:49)
The Technical Requirements (3:52)
The Class Structure (2:38)
The File Structure (2:56)
The File Paths (3:00)
The Code (5:08)
Iterate (9:08)
The code from this lesson
Outro (0:41)

Introduction to the course

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