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Bibliography - © Copyright 2022 – 2023. + © Copyright 2022 – 2024.

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Cite this Work - © Copyright 2022 – 2023. + © Copyright 2022 – 2024.

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Conda on Apple M1 Chip - © Copyright 2022 – 2023. + © Copyright 2022 – 2024.

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Using Conda - © Copyright 2022 – 2023. + © Copyright 2022 – 2024.

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Data# - © Copyright 2022 – 2023. + © Copyright 2022 – 2024.

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Using PIP - © Copyright 2022 – 2023. + © Copyright 2022 – 2024.

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Index

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Increase citations, ease review & foster collaboration - © Copyright 2022 – 2023. + © Copyright 2022 – 2024.

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Consent - © Copyright 2022 – 2023. + © Copyright 2022 – 2024.

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Disclaimer - © Copyright 2022 – 2023. + © Copyright 2022 – 2024.

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Ablation Studies - © Copyright 2022 – 2023. + © Copyright 2022 – 2024.

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Testing - © Copyright 2022 – 2023. + © Copyright 2022 – 2024.

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Interpretability - © Copyright 2022 – 2023. + © Copyright 2022 – 2024.

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Why make it reproducible? - © Copyright 2022 – 2023. + © Copyright 2022 – 2024.

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Machine Learning -
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Model Training - © Copyright 2022 – 2023. + © Copyright 2022 – 2024.

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1.3.5. Choosing the appropriate Evaluati

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{'fit_time': array([0.00573683, 0.00520396, 0.00519919, 0.00517201, 0.00513029]),
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@@ -1366,7 +1366,7 @@ 
1.3.8. Conclusion
     
-      © Copyright 2022 – 2023.
+      © Copyright 2022 – 2024.
       

     
   

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@@ -867,7 +867,7 @@ 
2.3.4. Linear and Standard Models
     
-      © Copyright 2022 – 2023.
+      © Copyright 2022 – 2024.
       

     
   

diff --git a/notebooks/3-model-sharing.html b/notebooks/3-model-sharing.html
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3.3.5. Docker for ultimate reproducibili
 
   

     
-      © Copyright 2022 – 2023.
+      © Copyright 2022 – 2024.
       

     
   

diff --git a/notebooks/4-testing.html b/notebooks/4-testing.html
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4.4.4. Input Data Validation
     
-      © Copyright 2022 – 2023.
+      © Copyright 2022 – 2024.
       

     
   

diff --git a/notebooks/5-interpretability.html b/notebooks/5-interpretability.html
index 4c0269c..4dca227 100644
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5.3.1. Partial Dependence for Machine Le
 

 

 
dict_keys(['grid_values', 'values', 'average'])
-Example Values: [36.  42.5 43.5 50.  52. ], Average: [2.22111957 2.22114964 2.21346532 1.69299685 1.67506995]
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@@ -830,7 +830,7 @@ 
5.3.2. Shap Inspection
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<shap.explainers._tree.TreeExplainer at 0x7fdcf9fbd5e0>
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@@ -864,7 +864,7 @@ 
5.3.2. Shap Inspection
 

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@@ -891,7 +891,7 @@ 
5.3.2. Shap Inspection
 

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5.3.3. Model Inspection
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tensor([[0.5477, 0.5859]], grad_fn=<SigmoidBackward0>)
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tensor([[0.3700, 0.5343]], grad_fn=<SigmoidBackward0>)
 

 

 

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5.3.3. Model Inspection
     
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6.2. Ablation Studies
     
-      © Copyright 2022 – 2023.
+      © Copyright 2022 – 2024.
       

     
   

diff --git a/resources/ablation.html b/resources/ablation.html
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@@ -517,7 +517,7 @@ 
6.3.1. Bibliography
     
-      © Copyright 2022 – 2023.
+      © Copyright 2022 – 2024.
       

     
   

diff --git a/resources/benchmarking.html b/resources/benchmarking.html
index a1d7556..6dc844b 100644
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2.4.1. Bibliography
     
-      © Copyright 2022 – 2023.
+      © Copyright 2022 – 2024.
       

     
   

diff --git a/resources/evaluation.html b/resources/evaluation.html
index 404f808..3bd55ff 100644
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1.4.1. Bibliography
     
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+      © Copyright 2022 – 2024.
       

     
   

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5.4.1. Bibliography
     
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3.4.1. Bibliography
     
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4.5.1. Bibliography
     
-      © Copyright 2022 – 2023.
+      © Copyright 2022 – 2024.
       

     
   

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6.1. Foster Collaboration
     
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Increase citations, ease review & collaboration – Making machine learn
 
   

     
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Real-world Perspectives to Avoid the Worst Mistakes using Machine Learning i
 
   

     
-      © Copyright 2022 – 2023.
+      © Copyright 2022 – 2024.