Sure. But you only get to do 60,000*20 model evals in total either way! (i.e if the 2nd order method needs twice as many evals, you only get 10 epochs)
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Random Seeds and Model Evaluation: The Coincidence Problem
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If you can find a random seed that by coincidence happens to get >94% of 60,000 10-class classification decisions correct then yes, that counts.
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Plain ResNet with GeneralRelu and 1Cycle Training
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It's the plainest possible resnet with GeneralRelu, adamw, and 1cycle training.
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Fair Compensation for Artists’ Work Used by AI Systems
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I think there's also a discussion about "can it be fair for people to benefit from artists' work without them being compensated", regardless of whether it's legal. I also think coders should feel the same way about this as they feel about their code being used by OpenAI Codex.
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Fashion-MNIST Challenge: Best Accuracy in 20 Epochs
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Challenge: what's the best accuracy (on the published test set) you can get on fashion-MNIST in 20 epochs, using a non-pretrained model? (Any self-supervision epochs you do will count in the 20 epoch limit.)
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Fine-tuned Models Testing on Public Datasets
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Interesting. What kind of data are you inferring on? Is there some publicly available data that you’re testing on? Would love to test out some of our fine-tuned models against it.
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New Math for Machine Learning and Data Science Course Launched
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New course announcement! Math for Machine Learning and Data Science. Designed to make learning AI's math easy: ∙ Linear algebra ∙ Probability & Stats
∙ Calculus Will help learners build better ML systems and pass job interviews! -
Build Image Classification Deep Learning Pipeline in 15 Lines
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Image classification is hard: Complex pipelines Need expert knowledge about images Weeks to train models But it doesn’t need to be. Learn to #build & #deploy an end-to-end deep learning pipeline <15 lines of code. And it's a fun use case! https://
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LLM Configuration Serialization in JSON and YAML Formats
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Serialization of LLM Configurations Have a favorite temperature/parameter setting for your LLM that you want store/version not in code? Now you can! @AkashSamant4 made it super easy to read/write LLM configurations to/from disk in json and yaml format