So what is game design? Simply speaking, game design is the process of applying design principles in order to create a game. This Free Code Camp article may help you understand the process of creating a game and what considerations you need to take.

To get started, you have to plan out your project. In order to be organized and keep track of all of your ideas, it’s a good idea to build a game design document. Check out this article from the National STEM Video Game Challenge for a description of game design documents and some helpful examples.

Next, you need to decide what tools you are using to build your game. Here is a list of game development tools. We highly recommend checking out Unity, a really powerful application to help you build beautiful and professional-level games quickly. If you’re interested, check out these tutorials for Unity development!

Finally, here’s a list of miscellaneous resources to help you get started with development:

• Introduction to Game Design in 3 Minutes
• Unity’s Game Developer Advice: A series of 4 videos from unity to get you started on developing your game
• Extra Credit’s video series on game development: Helpful videos discussing many aspects of Game Design and Development.
• This Reddit Game Design Guide: A very definitive and specific resource to help you on more specific problems you may encounter throughout your project
• The Game Maker’s Toolkit: A YouTube channel full of really useful critique and analysis of game elements and mechanics.
• GDC Vault: Talks from influential people in the game development industry.
• Noah Caldwell Gervais: In-depth gaming reviews.
• Magic: The Gathering Podcasts: Mark Rosewater’s (Designer of Magic: The Gathering) podcasts on game design.
• The Pretentious Game Design podcasts: Another great podcast on game design.

Good luck and happy hacking!

Thanks to Nitish Padavala (Cal Poly CS ‘21) for putting together this guide!

A Hacker’s Starter Pack for Game Design Hacks was originally published in SLO Hacks on Medium, where people are continuing the conversation by highlighting and responding to this story.

IoT stands for the “Internet of Things”, it incorporates objects like fridges, toasters, thermostats, and anything else that can be made “smart” through software. A very common IoT device category that you may know is the smart assistant which includes products like the Amazon Alexa or Google Home. These IoT devices communicate with many other things and can integrate well with products like smart light bulbs, smart outlets, and much more. If you want to learn more about the IoT and how it is changing the way we do business and live you can check out these articles:

• https://www.zdnet.com/article/what-is-the-internet-of-things-everything-you-need-to-know-about-the-iot-right-now/
• https://www.recode.net/2015/1/15/11557782/a-beginners-guide-to-understanding-the-internet-of-things

IoT hacks fall under two main categories. You could build something for an IoT device, such as making a new Alexa Skill, or you could make a unique smart object. An example of this might be making a water bottle that learns to cool itself in different temperature settings.

An IOT hack requires a few things:

• The IoT hardware itself
• A programming language
• A unique idea
• * A device to control the hardware
• ** An API to use

* this is only necessary if you are trying to make a new IOT device

** this is only necessary if you are going to develop something new for a device or company that is already in the IoT space

As for hardware to use, there are many options. At SLO Hacks, we will have the 2019 MLH Hardware lab available. This google doc has a list of all the hardware provided to you during the course of the hackathon. It may be useful to look over this list and see what hacks you could put together with these devices. If you are looking for specific boards/kits to use, this guide can help you choose the hardware that is right for your project. If you are looking for ideas for projects using Raspberry Pis or Arduinos here is a list of some helpful sites:

• Pi My Life Up: This has open and closed source projects.
• Adafruit: They have guides, videos, forums, and blogs about building iot projects with Raspberry Pis.
• Arduino Project Hub: This site has around 200 project outlines and guides.

Since many technological solutions now involve connected devices, it can be helpful to use one of the many IoT applications. Cloud hosting has become a wide-spread and generally appreciated method of developing and running various technology solutions, and IoT (which directly depends on the Internet) definitely benefits from all the advantages of cloud computing. There are special cloud-based IoT platforms that support the Internet-based functions of the application running, maintenance, analytics, data storage, and security measures. You may find these platforms helpful in building your IoT Hacks:

1. Google Cloud:

• Cloud IoT Core allows connecting various devices and gathering their data.
• Cloud Pub/Sub processes event data and provides real-time stream analytics.
• Cloud Machine Learning Engine allowing the building of ML models and use of the data received from IoT devices.

2. Amazon Web Services (AWS):

• AWS IoT Core allows devices to connect to the Internet and to each other and exchange data.It also enables communication between devices from different manufacturers.
• AWS IoT Device Management allows easy addition and organization of devices.
• AWS IoT Analytics providing a service for automated analytics of large amounts of various IoT data.

For more information about other IoT platforms such as Cisco IoT Cloud Connect, IBM Watson IoT, and Microsoft Azure IoT check out this article.

Finally, here are some miscellaneous resources and communities for building IoT projects.

1. Hackerster.io has project ideas and outlines. It is a community all about how people have hacked together IoT projects. There are lots of pictures and in depth descriptions of past projects.
2. IoT For All looks at IoT topics like healthcare, manufacturing, supply chain, and infrastructure. It also looks at IoT strategy, analytics, and what the internet of things means for actual people.
3. The IoT magazine has a number of quick reads and cool articles that may be useful to learn more about IoT.
4. The r/IOT subreddit is completely dedicated to the internet of things.

Good luck and happy hacking!

Thanks to Emily O’Neal (Cal Poly CS ‘21) for putting together this guide!

A Hacker’s Starter Pack for IoT & Hardware Hacks was originally published in SLO Hacks on Medium, where people are continuing the conversation by highlighting and responding to this story.

First things first: most machine learning is done in Python, so if you haven’t touched that in a while, it’s probably a good idea to refresh your memory with a resource like LearnPython.

Alright, now we get to our first decision point. There are two strategies to incorporate AI & ML into your hack: you can build a neural network from scratch or you can use pre-trained networks from an API. If the thing you want to do is relatively simple, and lots of work has been done in that domain already, it is likely that a pre-trained model exists for your use-case. However, if the task you want your model to perform is complex or highly specific scenario, it is unlikely that a pre-trained network will do the job, and you’ll need to put together the pieces yourself. If you think there might be a pre-trained network that covers your use-case, check out the model zoo at https://modelzoo.co/, a website that shares open-source network architectures and pre-trained weights. Each model in the zoo will direct you to the git repo where that model can be found as well as instructions for running the model.

If your task is unique or you’re just really interested in how these neural networks work, here’s a list of resources to help get you started building your own:

• Andrej Karpathy’s Hacker’s Guide to Neural Networks: A great introductory guide to teach you the basics written by one of the masters. It contains detailed descriptions that help build an intuitive understanding of neural networks from the ground up.
• The Pytorch 60 Minute Blitz: This tutorial series from Pytorch (one of the main machine learning frameworks) exposes you to the basics with tons of example code and gives you everything you need to get started with the framework in just an hour (though account for a little extra time to install packages and get everything working).
• The Rest of the Pytorch Tutorials: Once you’ve hit all the basics with the 60 minute blitz, pick up one of their more challenging tutorials to learn more complex topics like neural style transfer!
• Tensorflow Tutorials: As an alternative to Pytorch, Tensorflow is another great machine learning framework. Check out these tutorials to get started with it!
• OpenAI’s Spinning Up in Deep Reinforcement Learning: If you want to create an agent to play a game or make decisions based on their environment, check out OpenAI’s extensive beginner’s guide to the field of reinforcement learning!

If you already have experience with machine learning and artificial intelligence, here are some projects from Stanford’s machine learning courses to serve as inspiration (look for the cool ideas you could iterate upon, or apply to a new domain):

• Artificial Intelligence (229):
• 2011 projects
• Natural Language Processing (224n):
• 2015 projects
• Computer Vision (231n):
• 2017 projects
• 2016 projects
• 2015 projects

Machine learning doesn’t work without data, and sometimes finding an interesting dataset can spark a great idea for a hack, so here is a list of resources to help you find applicable datasets:

• Kaggle: the one-stop-shop for all kinds of data science challenges and fun datasets.
• Google Dataset Search: Google’s tool for pulling the dataset you need from the depths of the interwebs.
• ImageNet: The famous (and massive) collection of labeled images used for all kinds of detection and classification tasks.
• UCI Machine Learning Dataset Repository: A collection of datasets with a very wide variety of problem domains.
• Stanford NLP Resource List: Sources of text data used by Stanford’s NLP lab

Finally, some miscellaneous resources to take a look at if you’re still looking for things to read:

• An Introduction to GANs: Learn how to create images without any labels.
• Awesome Deep Vision: “A curated list of deep learning resources for computer vision.”
• r/MachineLearning: Reddit’s machine learning community.
• r/learnmachinelearning: Reddit’s community of machine learning students
• The Deep Learning Book: This textbook on machine learning is a fantastic resource for those with a solid background in statistics and mathematics. It explains a lot of difficult concepts at very detailed levels. It probably is not a great resource for hackers to digest information quickly, but if you want to understand what is really going on under the hood and why all these bells and whistles actually work, read this.

Good luck and happy hacking!

Thanks to Jackson Waschura (Cal Poly CS 21’) for putting together this guide!

A Hacker’s Starter Pack for AI & ML Hacks was originally published in SLO Hacks on Medium, where people are continuing the conversation by highlighting and responding to this story.

You might be wondering, what’s a hackathon? Check out Dave Fontenot’s post detailing hackathons. TL;DR: 24–36 hour events where people can build anything they want — augmented reality games, robotic arms, Tinder for dogs, you name it.

As a high schooler, I was upset that at most hackathons, I’d never see familiar faces, that no one would introduce themselves to me and say “Hey, I’m from Los Altos High, too!”, that I’d fly or drive alone. Thankfully, the hackathon community was and still is welcoming and inclusive to everyone. I’ve met students founding clubs and companies, mentors kicking ass in their professional lives, sponsors giving back to the hackathon community.

I founded and ran Los Altos Hacks during my senior year, hoping that more students from my high school would become interested in hackathons. Long story short — it worked, and I ended up seeing a lot more students from my high school being active in the hackathon community.

Unsurprisingly, I had a similar problem at my college, Cal Poly SLO. You’d think that at an university five times bigger than my high school, there’d be more students passionate about hackathons.

There was another hackathon that was more product-focused and didn’t embody the hackathon community I saw at other collegiate hackathons. I wanted something that prioritized technical achievement, something that included the worldwide hacker community.

January 2017: I found a group of seven people who were interested in starting a hackathon with me.

February 1, 2017: The seven of us had a meeting, where we came up with the name “SLO Hacks”.

Fast forward a year to February 3, 2018: SLO Hacks 2018, a 200-student, 24-hour collegiate hackathon, is finally happening.

SLO Hacks. Our mission used to be hosting one yearly event, but now, we’re a Cal Poly club hosting quarterly hackathons, a life-changing experience to beginner and veteran coders alike, and a movement bridging San Luis Obispo’s community with the rest of the world.

We have a few goals:

1. To bring the hackathon community we see around California, around the USA, and heck, even around the world, right here to San Luis Obispo
2. To inspire students in San Luis Obispo to start attending more hackathons not only in SLO, but also out of town
3. To give students an opportunity to have fun and build anything they want over a weekend
4. To champion underrepresented minorities and majors at our events — we truly aspire to be an inclusive event and club

One event down, but this is just the beginning. Small town, big ideas — we’re going to change Cal Poly.

If you’d like to hear more about SLO Hacks or have any questions, tweet me @selynnasun!

SLO Hacks? What’s that? was originally published in SLO Hacks on Medium, where people are continuing the conversation by highlighting and responding to this story.