🤑 Blackjack with Artificial Intelligence (CS )

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But Python could load the model and predict with ease. Running multiple thousand round simulations, Marvin would even beat the standard AI on some occasions. I really wanted to be able to get model predictions using Go code so I could remove the command line Python nonsense, which was really slow because it was loading the model every. Atoi strings.

Seeing as re:Invent was held in Vegas, I decided to take the spirit of Vegas home with me and create my own text-based blackjack game in Go.

So what did I do? I had another hackathon coming up at work and I thought it would be cool to try and train a model to play a better game of blackjack using SageMaker.

Fortunately, I was able to use all the same hyperparameters. This was a huge success and a tremendous breakthrough in speed, but I also wanted Marvin to perform better. SageMaker blackjack ai me to quickly get up and running with machine learning and provided access to powerful computing resources.

This resulted blackjack ai a jump in how well the AI performed! I think with some work, Marvin could become a world champion.

After automated rounds, here are the results. My goals for the hackathon were the following: Explore SageMaker's training capabilities Generate copious amounts of blackjack game data Train a model using the game data Use predictions from the model to create a blackjack AI First, I instrumented my blackjack game to record dealer and player hands, as well as the outcome of their next move.

I recommend checking out the full repo here. These resulted in 2, rows that became my training data. Larry is an idiot who picks randomly whether to hit or stay. Coder's Haven. TrimSpace string out if err! Also goes to show that gambling is not a viable career move.

I downgraded my XGBoost version to 0. Deploying the SageMaker model to an endpoint was just another simple command and then I was able to see some predictions.

Remember, Marvin is the one using the trained model. CombinedOutput if err! Marvin is an AI making decisions using predictions from my model. Casino image from bestcasinosites. I ran a simulation with a million rounds and here are the results:.

I realized I had a few small problems related to the format of my training data needed to be integers, not stringsbut I learned and wrote some code to translate the training data.

XGBoost updated to version 1. The Go packages still had issues loading the model for various reasons. I ran a simulation of 1 million rounds with two AI opponents, one that picks moves randomly and one that plays using the generally accepted best strategy.

I don't really know. Not bad for a first pass. Once the AI was done, I ran a https://aktau-site.ru/blackjack/casino-slot-blackjack-roulette-apk.html to see how the model performed.

I was impressed that the model correctly suggested splitting double aces! I added a simple interface so it would be easy to create different AI opponents. He's actually winning more blackjack ai and losing less games than Joe, percentage-wise, but he's still losing more money due to poor double down decisions, etc.

First, I instrumented my blackjack game to record dealer and player hands, as well as the outcome of their next move. This concluded the hackathon, but I wasn't quite done yet. Joe plays using the generally accepted best strategy. Command ". Marvin still isn't performing quite as well as the standard blackjack strategy Joebut he's getting there!

Serialization in Python is called pickling and unpickling. For hefty training jobs, it may prove to be a valuable tool. Next step was to load the model using Go and get predictions locally. Unfortunately, due to mismatched XGBoost versions, machine differences, and unpickling problems, I was unable to load the model locally.

So I decided to just call the Python blackjack ai from Go via command line don't do this at home, kids. Final step in the process was to create an AI that continue reading the predictions from the trained model.

This was a really fun project to work on and it was really satisfying to see good results as it progressed. Share this.

I fiddled with the AI a little bit more and adjusted it to use multiple predictions, instead of just the prediction with the highest score, and pick the highest scored prediction with a favorable result.