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Correlation != Predictiveness
Here’s how to measure predictiveness.
13 hrs ago
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Avi Chawla
22
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Correlation != Predictiveness
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Is Your Model Data Deficient?
More data may not always help.
Mar 25
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Avi Chawla
31
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Is Your Model Data Deficient?
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When is Random Splitting Fatal for ML Models?
Here's when to avoid it.
Mar 23
•
Avi Chawla
31
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When is Random Splitting Fatal for ML Models?
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11 Powerful Techniques to Supercharge Your ML Models
Take your ML models to the next level.
Mar 22
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Avi Chawla
36
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11 Powerful Techniques to Supercharge Your ML Models
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Skorch: The Power of PyTorch Combined with The Elegance of Sklearn
The best of both worlds.
Mar 20
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Avi Chawla
33
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Skorch: The Power of PyTorch Combined with The Elegance of Sklearn
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The Probe Method: An Intuitive Feature Selection Technique
Introduce a bad feature to remove other bad features.
Mar 19
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Avi Chawla
23
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The Probe Method: An Intuitive Feature Selection Technique
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7
Using Proxy-Labelling to Identify Drift
An intuitive way to detect drift.
Mar 18
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Avi Chawla
30
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Using Proxy-Labelling to Identify Drift
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Why Mean Squared Error (MSE)?
Why not any other loss function?
Mar 17
•
Avi Chawla
39
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Why Mean Squared Error (MSE)?
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Breathing KMeans vs KMeans
Robustify KMeans with centroid addition and removal.
Mar 16
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Avi Chawla
29
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Breathing KMeans vs KMeans
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From PyTorch to PyTorch Lightning
Simplify deep learning model building and training with PyTorch Lightning.
Mar 13
•
Avi Chawla
30
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From PyTorch to PyTorch Lightning
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The Utility of ‘Variance’ in PCA for Dimensionality Reduction
Here's why using variance makes sense in PCA.
Mar 12
•
Avi Chawla
31
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The Utility of ‘Variance’ in PCA for Dimensionality Reduction
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The Categorization of Clustering Algorithms in Machine Learning
6 types of clustering algorithms in a single frame.
Mar 10
•
Avi Chawla
41
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The Categorization of Clustering Algorithms in Machine Learning
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