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⌨️ Build a LLM App - Grocery List Organizer
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Classroom Contents
Building AI Applications Locally with Ollama - From Setup to Advanced Projects
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- 1 ⌨️ Intro
- 2 ⌨️ What Is this course about?
- 3 ⌨️ Course Prerequisites
- 4 ⌨️ Development Environment Setup
- 5 ⌨️ Ollama Deep Dive
- 6 ⌨️ Ollama Key Features
- 7 ⌨️ Ollama Setup
- 8 ⌨️ Download Ollama Locally
- 9 ⌨️ Ollama Models - How to Pull Different Ollama Models Locally
- 10 ⌨️ LLM Parameters Deep Dive
- 11 ⌨️ Understanding Model Benchmarks
- 12 ⌨️ Ollama Basic CLI Commands - Pull and Testing Models
- 13 ⌨️ Pull in the Llava Multimodal MOdel and Captioning an Image - Hands-on
- 14 ⌨️ Summarize and Sentiment Analysis and Customizing Models with the Modelfile
- 15 ⌨️ Ollama REST API
- 16 ⌨️ Ollama REST API - Request JSON
- 17 ⌨️ Ollama Models Support Different Tasks - Summary
- 18 ⌨️ Different Ways to Interact with Ollama Models - Overview
- 19 ⌨️ Ollama Model Running Under Msty App - Frontend Tool - RAG Hands-on
- 20 ⌨️ Introduction to Python Library for Building LLM Applications Locally
- 21 ⌨️ Interact with Llama3 in Python using Ollama REST API
- 22 ⌨️ Ollama Python Library Chatting with our Model
- 23 ⌨️ Chat Example with Streaming
- 24 ⌨️ Using Ollama Show Function
- 25 ⌨️ Create a Custom Model in Code
- 26 ⌨️ Build a Real-world Use case Application - Introduction
- 27 ⌨️ Build a LLM App - Grocery List Organizer
- 28 ⌨️ Building RAG Systems with Ollama - Overview of RAG Systems and Langchain Crash Course
- 29 ⌨️ Deep Dive into Vectorstore and Embeddings - the Whole Picture - Crash Course
- 30 ⌨️ Overview of Our PDF RAG System We will be Building
- 31 ⌨️ Set up our RAG System - Document Ingestion and Vector DB Creation and Embeddings
- 32 ⌨️ RAG System - Retrieval and Querying - Final
- 33 ⌨️ RAG System - Cleaner Code Code Refactoring
- 34 ⌨️ RAG System - Streamlit Version
- 35 ⌨️ BONUS for YOU!
- 36 ⌨️ Introduction to the Next Application - AI Recruiter Agency
- 37 ⌨️ Building the AI Recruiter Agency
- 38 ⌨️ Outro - Final Thoughts and Your Bonus - Thank you!
