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2 Techniques to Synchronize ML Models in Multi-GPU Training
...explained visually.
Jul 10
•
Avi Chawla
1
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2 Techniques to Synchronize ML Models in Multi-GPU Training
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DropBlock vs. Dropout for Regularizing CNNs
Addressing a limitation of Dropout when used in CNNs.
Jul 9
•
Avi Chawla
3
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DropBlock vs. Dropout for Regularizing CNNs
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A Hands-on Demo on Autoencoders
...along with applications.
Jul 8
•
Avi Chawla
5
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A Hands-on Demo on Autoencoders
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Bias-Variance Tradeoff is Incomplete!
A counterintuitive phenomenon while training ML models.
Jul 7
•
Avi Chawla
28
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Bias-Variance Tradeoff is Incomplete!
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15 Techniques to Optimize Neural Network Training
...explained in a single frame.
Jun 27
•
Avi Chawla
4
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15 Techniques to Optimize Neural Network Training
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Package AI/ML Projects with KitOps MCP Server
100% open-source and a better alternative to Docker.
Jun 24
•
Avi Chawla
8
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Package AI/ML Projects with KitOps MCP Server
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1
11:13
Clean ML Datasets With Cleanlab
...in just 4 lines of Python code.
Jun 13
•
Avi Chawla
4
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Clean ML Datasets With Cleanlab
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48 Most Popular Open ML Datasets
...summarized in a single frame.
Jun 2
•
Avi Chawla
12
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48 Most Popular Open ML Datasets
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An Animated Guide to KMeans
In 3Blue1Brown style.
May 25
•
Avi Chawla
5
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An Animated Guide to KMeans
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1:41
Random Forest vs. ExTra Trees
"ExTra" does not mean more.
May 14
•
Avi Chawla
2
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Random Forest vs. ExTra Trees
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Zero-inflated Regression
What it is and how it ruins ML modelling?
May 8
•
Avi Chawla
3
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Zero-inflated Regression
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Memory Pinning to Accelerate Model Training
A simple technique, and some key considerations.
May 7
•
Avi Chawla
5
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Memory Pinning to Accelerate Model Training
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