Table Of Contents - Budget-Friendly Ways To Build AI
What Readers' Journey Will Look Like Reading My Series
Have You Ever Played Yoshi Island?
Multiple “Worlds”, Each With Several “Stages”
In Yoshi Island, game by Nintendo and probably my favorite childhood video game, it has multiple worlds with multiple stages of its own that a player goes through in order. Each stage can be played separately without a problem but the story is just much more understandable if you play in the right order.
For this series, let’s just call each “world” a section and “stage” an article.
I’ll be covering each of the topic in the below diagram per section, where each section will have several articles dedicated to it. Since each topic spans different amount of materials, number of articles per section will vary. What I can say for sure is that readers should expect me to cover - important scaling factors, technicalities and team management skills that are involved to effect those scaling factors, and risk management tactics.
For an example, with the “Data Pipelining” Section, I’ve already covered a first article here. There are couple more to be covered in this section before we transition to the "Understanding Data” Section. However, I think the “Understanding" Data” Section may be shorter than the “Data Pipelining” Section.
Bonus Contents Are Helpful & They Will Be Delivered In Many Formats
There will occasionally be some bonus contents that will help advance reader’s understanding of specific concepts beyond the basics or give them fresh perspectives.
I expect what would be covered has a wide variety. Format of these contents can vary. But they will be delivered in ways that I and readers believe are the most effective.
What’s covered will be chosen based on a combination of what I feel is appropriate + reader feedback. It’s just going to be a bit experimental by nature.
Each World Will Require You To Put On Different Hats
Each “World”, because they cover different topics, will be different. Sometimes it’s a matter of types of skills or competencies involved. But it’s mostly because they require you to think differently. Data engineering and model training are, of course, very different - one is engineering heavy the other research heavy. I can also say that parts that require engineering mindset won’t be all alike - data engineering is very different from agent design. One is more data mindset the other systems mindset.
Up, Down, Left, Right - All the Buttons Are The Same
What’s good news is that readers will be able to navigate every “worlds” as long as they have the basics.
Being able to read English.
Having worked in a team before.
Knowing a thing or two about data - that they need to be stored somewhere and be sent to different places, that it takes time and money to store and transfer, and that it takes time and money to use the data.
Big Bad Boss = Just Understanding The Basic Concepts
This series is meant to be in easy mode.
I’m writing this series so really anyone can learn how to build AI cheaply. There are plenty of resources that teach the technical skills - how to use Python, what packages to use, how to troubleshoot when using those packages, etc…
I can promise that the Big Bad Boss you’re looking to defeat doesn’t require picking up bunch of technical jargons. You should be able to understand the basics of what it takes to develop your own AI in your room or your garage if you’re old-fashioned. I want everyone to do this without actually understanding any jargons.
Welp, hope you enjoy :) And leave comments or messages if you think you don’t understand something. I’m on here often enough.