data_engineering_on_gcp_book VS shotcaller

This book will walk you through setting up a complete data engineering stack on GCP: https://github.com/Nunie123/data_engineering_on_gcp_book

As for resources, this book goes over a lot of these: https://github.com/Nunie123/data_engineering_on_gcp_book. However, this goes over the 'how', not the 'why'. The only method I know for understanding the 'why' is experience. Whether at work or personal projects.

Here's a good book to follow along to introduce you to common tooling and design patterns: https://github.com/Nunie123/data_engineering_on_gcp_book

I'm not sure if this is exactly what you're looking for, but here's a book on GitHub that talks about the tools and steps for building data pipelines into a data warehouse: https://github.com/Nunie123/data_engineering_on_gcp_book

Check out this book: https://github.com/Nunie123/data_engineering_on_gcp_book

If you're interested in example of how to build a complete data engineering infrastructure, you should check out this book: https://github.com/Nunie123/data_engineering_on_gcp_book

If you want to try Airflow without the setup headache, you can try Composer on GCP, which is a hosted version of Airflow. I wrote some info on how to do that here: https://github.com/Nunie123/data_engineering_on_gcp_book/blob/master/ch_2_orchestration.md

This book might be a good resource for you: https://github.com/Nunie123/data_engineering_on_gcp_book

If you want a place to start on personal projects you can check out this book, https://github.com/Nunie123/data_engineering_on_gcp_book, which will walk you through the basics of setting up a full data engineering stack.

If you are interested in tooling, here's a free book on setting up a basic data engineering tech stack on GCP: https://github.com/Nunie123/data_engineering_on_gcp_book

As for a project using these, see: https://github.com/amethyst/shotcaller and https://github.com/jojolepro/minigene :)

We do indeed intend to be on the lookout for such opportunities for standardization. Our main R&D project in this regard is Shotcaller, which is made with bracket-lib by people who have previously worked with Amethyst Engine.

https://github.com/amethyst/shotcaller

We’re happy to help any newcomers along on our Discord: https://discord.gg/qvJyTYM

I’m building a minimalistic, 1v1 MOBA game (Dota/LoL) that’s all about grand strategy at the macro level, like chess. It is designed from scratch to accommodate AI development.

OpenAI gave up after beating 99% of players in a limited version of DOTA2. They essentially just figured out how to out-micro human players. We want to let players play alongside AI assistance, like a racing car driver backed up by their team of mechanics and engineers.

https://github.com/amethyst/shotcaller

Make a new 🦹 Leader or 📦 Item!

Make a new 🦹 Leader or 📦 Item!

I’m working on one such modern RTS game: https://github.com/amethyst/shotcaller

It’s a MOBA-style game that is played 1v1, with the 5 “players” on each side controlled by autonomous bots. This design accommodates AI development as part of the sport, much like a F1 driver and their team of engineers and mechanics.

The game is written in Rust and will use WASM for scripting to accommodate a wide range of languages for both game modding and AI code. While it’s only 1v1 in its initial iteration, I agree that there’s immense value in cooperative and more micro-level play, so we do intend to incrementally move towards that as an alternative game mode.

I’d love to chat more with anyone interested in this particular design or RTS/MOBAs in general. You can find my email on my GitHub.