Towards-Explainable-AI-System-for-Traffic-Sign-Recognition-and-Deployment-in-a-Simulated-Environment
ML.NET-Auto-ML-ESRB-Rating-Classification
| Towards-Explainable-AI-System-for-Traffic-Sign-Recognition-and-Deployment-in-a-Simulated-Environment | ML.NET-Auto-ML-ESRB-Rating-Classification | |
|---|---|---|
| 2 | 3 | |
| 45 | 3 | |
| - | - | |
| 0.0 | 0.0 | |
| almost 3 years ago | about 2 years ago | |
| C# | C# | |
| MIT License | - |
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Towards-Explainable-AI-System-for-Traffic-Sign-Recognition-and-Deployment-in-a-Simulated-Environment
- Simulation based Traffic Sign Recognition Benchmark - A simulation framework developed for training autonomous-driving systems for traffic sign recognition
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Simulation-based Traffic Sign Recognition Benchmark (STSRB)
Check out the GitHub link for more information: https://github.com/alen-smajic/Towards-Explainable-AI-System-for-Traffic-Sign-Recognition-and-Deployment-in-a-Simulated-Environment
ML.NET-Auto-ML-ESRB-Rating-Classification
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The 3 Core Machine Learning Tasks
This trained model would then be able to predict ESRB ratings for video games that had yet to be released and generate some degree of probability that a game might be in any given rating.
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What can you do in ML.NET with C#?
For more code examples around multi-class classification, take a look at my article and video on using AutoML and ML.NET to predict ESRB ratings for video games which also serves as an in-depth introduction to ML.NET for a single task.
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Using C# and Auto ML in ML .NET to Predict Video Game Ratings
This article comes with an accompanying GitHub repository containing a .NET 6 console app that can train itself to evaluate video games and predict an ESRB rating for games the trained model hasn't seen before.
What are some alternatives?
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MLBox - MLBox is a powerful Automated Machine Learning python library.
Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning - My Computer Vision project from my Computer Vision Course (Fall 2020) at Goethe University Frankfurt, Germany. Performance comparison between state-of-the-art Object Detection algorithms YOLO and Faster R-CNN based on the Berkeley DeepDrive (BDD100K) Dataset.
nylon - An intelligent, flexible grammar of machine learning.