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Are you a scientist applying ML?
I wrote a tutorial with ready-to-use notebooks to make your life easier!
Let's focus on 3 aspects:
• More Citations
• Easier Review
• Better Collaboration
Let's see how:
I wrote a tutorial with ready-to-use notebooks to make your life easier!
Let's focus on 3 aspects:
• More Citations
• Easier Review
• Better Collaboration
Let's see how:
First things first:
This was a @EuroSciPy tutorial in 2022.
In the future, a talk recording will be available. Until then here's the gist:
1. Model Evaluation
2. Benchmarking
3. Model Sharing
4. Testing
5. Interpretability
6. Ablation
#euroscipy
github.com/JesperDramsch/…
This was a @EuroSciPy tutorial in 2022.
In the future, a talk recording will be available. Until then here's the gist:
1. Model Evaluation
2. Benchmarking
3. Model Sharing
4. Testing
5. Interpretability
6. Ablation
#euroscipy
github.com/JesperDramsch/…
@EuroSciPy 📐 Model Evaluation
In science, we want to describe the world.
Overfitting gets in the way of this.
With real-world data, there are many ways to overfit, even if we use a random split and have a validation and test set!
Save yourself the pain!
github.com/JesperDramsch/…
In science, we want to describe the world.
Overfitting gets in the way of this.
With real-world data, there are many ways to overfit, even if we use a random split and have a validation and test set!
Save yourself the pain!
github.com/JesperDramsch/…
