🚀
10 Days Realtime LLM Bootcamp
  • Introduction
    • Getting Started
    • Course Syllabus
    • Course Structure
    • Prerequisites
    • Greetings from your Instructors
    • First Exercise (Ungraded)
  • Basics of LLM
    • What is Generative AI?
    • What is a Large Language Model?
    • Advantages and Applications of Large Language Models
    • Bonus Resource: Multimodal LLMs
  • Word Vectors Simplified
    • What is a Word Vector
    • Word Vector Relationships
    • Role of Context in LLMs
    • Transforming Vectors into LLM Responses
      • Neural Networks and Transformers (Bonus Module)
      • Attention and Transformers (Bonus Module)
      • Multi-Head Attention and Further Reads (Bonus Module)
    • Let's Track Our Progress
  • Prompt Engineering
    • What is Prompt Engineering
    • Prompt Engineering and In-context Learning
    • Best Practices to Follow in Prompt Engineering
    • Token Limits in Prompts
    • Prompt Engineering Excercise
      • Story for the Excercise: The eSports Enigma
      • Tasks in the Excercise
  • Retrieval Augmented Generation and LLM Architecture
    • What is Retrieval Augmented Generation (RAG)?
    • Primer to RAG Functioning and LLM Architecture: Pre-trained and Fine-tuned LLMs
    • In-Context Learning
    • High level LLM Architecture Components for In-context Learning
    • Diving Deeper: LLM Architecture Components
    • LLM Architecture Diagram and Various Steps
    • RAG versus Fine-Tuning and Prompt Engineering
    • Versatility and Efficiency in Retrieval-Augmented Generation (RAG)
    • Key Benefits of RAG for Enterprise-Grade LLM Applications
    • Similarity Search in Vectors (Bonus Module)
    • Using kNN and LSH to Enhance Similarity Search in Vector Embeddings (Bonus Module)
    • Track your Progress
  • Hands-on Development
    • Prerequisites
    • Dropbox Retrieval App in 15 Minutes
      • Building the app without Dockerization
      • Understanding Docker
      • Using Docker to Build the App
    • Amazon Discounts App
      • How the Project Works
      • Step-by-Step Process
    • How to Run the Examples
  • Live Interactions with Jan Chorowski and Adrian Kosowski | Bonus Resource
  • Final Project + Giveaways
    • Prizes and Giveaways
    • Tracks for Submission
    • Final Submission
Powered by GitBook
On this page
  • Understanding Key Docker Terminologies
  • Resources to Understand Docker Better
  1. Hands-on Development
  2. Dropbox Retrieval App in 15 Minutes

Understanding Docker

This module will help you build the previous file if you're new to Docker and are struggling to install dependencies on your machine.

First off, a quick recap.

Think of Docker as a shipping container for your app. Just as a shipping container can hold all sorts of goods (clothes, electronics, etc.) and be transported anywhere in the world, Docker bundles your app and everything it needs to run into a 'container.' This makes it easy to share and run your app on any computer.

Given the complexities and manual effort involved in resolving dependency issues in your system, Docker can be a beneficial tool to standardize the development environment among all students.

Why Use Docker?

  • Standardized Environment: Everyone gets the same set of dependencies, reducing "it works on my machine" issues.

  • Isolated: Doesn't interfere with other projects or system-wide settings.

  • Ease of Use: Running the project becomes much simpler once set up.

Understanding Key Docker Terminologies

  • Docker Image: Consider this a blueprint or a container snapshot, including the application and its dependencies. You build an image once and use it to create multiple containers.

  • Docker Container: A container is a running instance of an image. It's a lightweight, stand-alone, executable software package with everything needed to run the code.

  • CMD: In Docker, the CMD instruction specifies the command to execute when the container starts up.

  • Docker Compose: A tool for defining and running multi-container Docker applications. Using a YAML file (docker-compose.yml), it allows you to specify how different containers interact with each other, making it easier to manage multiple containers as a single service.

Resources to Understand Docker Better

  • Basic Tutorial on Dockerfile: Here

  • Basic Tutorials on Docker Compose: Part 1 using (Single Container), Part 2 (using 2 Containers)

  • Blog on using ChatGPT to build an optimized Docker Image: 3-Minute Read

Now let's see the step-by-step implementation.

PreviousBuilding the app without DockerizationNextUsing Docker to Build the App

Last updated 1 year ago