Category Archives: Machine Learning

compute_total_loss

Posted on May 2, 2023 by tim

You’re here because you can’t get the unit tests for the Coursera Improving Deep Neural Networks course, Week 3, exercise number 1, to pass. You are trying to correctly implement def compute_total_loss(logits, labels): And the unit test keeps failing with … Continue reading →

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AWS EC2 GPU instance comparison

Posted on April 17, 2023 by tim

These are the results from running the ml-style-transfer project on three different AWS EC2 instance types. Instance Name $Cost/hour 250 epochs 2,500 epochs 50,000 epochs p3.2xlarge $3.06 14s$0.0119 55s$0.0468 928s$0.7888 t2.large $0.093 849s$0.0219 14,676s$0.3791 293,520s(extrapolated)$7.5826 c5.4xlarge $0.68 221s$0.0417 2,152s$0.4065 43,040(extrapolated)$8.1298 … Continue reading →

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Read, Do, Aha

Posted on April 8, 2023 by tim

This is a variation of “Be, Do, Have” (“Be, Do Have” == Be a photographer, Do take a bunch of photos, and then Have/Buy expensive equipment). It records my recent epiphany in Machine Learning. This variation is “Read, Do, Aha”. … Continue reading →

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Kaggle, JSON, Python, and pandas

Posted on March 17, 2023 by tim

While looking at various datasets from kaggle to do some experiments with Python and graph visualization with networkx, the arXiv dataset caught my attention. It has a (relatively) simple schema – authors, papers, and categories. It is also huge – … Continue reading →

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