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All-Reduce and Ring-Reduce for Model Synchronization in Multi-GPU Training
Two synchronization algorithms for intermediate-ML models.
Jul 25
22
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All-Reduce and Ring-Reduce for Model Synchronization in Multi-GPU Training
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Conformal Predictions: Build Confidence in Your ML Model's Predictions
A step towards building and using ML models reliably.
Jul 22
•
Avi Chawla
26
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Conformal Predictions: Build Confidence in Your ML Model's Predictions
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Quantization: Run ML Models on Tiny Hardware
A must-know skill for ML engineers.
Jul 15
•
Avi Chawla
21
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Quantization: Run ML Models on Tiny Hardware
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Batch Inference with MyMagic.AI API
World's cheapest batch inference.
Jul 8
•
Avi Chawla
28
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Batch Inference with MyMagic.AI API
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Introduction to Federated Learning
A step towards privacy-preserving ML.
Jun 26
•
Avi Chawla
29
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Introduction to Federated Learning
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4 Ways to Test ML Models in Production
...explained visually
Jun 21
•
Avi Chawla
31
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4 Ways to Test ML Models in Production
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A Unique Perspective on What Hidden Layers and Activation Functions Do
Intuitive guide to handling non-linearity with neural networks.
Jun 14
•
Avi Chawla
31
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A Unique Perspective on What Hidden Layers and Activation Functions Do
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A Practical Guide to Scaling ML Model Training
GPUs - GPU Clusters - Distributed Training.
Jun 13
•
Avi Chawla
24
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A Practical Guide to Scaling ML Model Training
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4 Strategies for Multi-GPU Training
...explained visually.
Jun 7
•
Avi Chawla
25
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4 Strategies for Multi-GPU Training
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An Intuitive Guide to Non-Linearity of ReLU
Here's why ReLU is a non-linear activation function.
Jun 5
•
Avi Chawla
22
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An Intuitive Guide to Non-Linearity of ReLU
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Knowledge Distillation for Model Compression
A practical walkthrough
Jun 4
•
Avi Chawla
23
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Knowledge Distillation for Model Compression
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Implementing KANs From Scratch Using PyTorch
A step-by-step demonstration of KANs.
Jun 1
•
Avi Chawla
28
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Implementing KANs From Scratch Using PyTorch
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