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Updated
Jul 15, 2021 - Python
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ml-platform
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Build and manage real-life data science projects with ease.
python
productivity
data-science
machine-learning
r
ai
reproducible-research
ml
rstats
r-package
model-management
ml-infrastructure
mlops
ml-platform
Determined: Deep Learning Training Platform
kubernetes
machine-learning
deep-learning
tensorflow
pytorch
hyperparameter-optimization
hyperparameter-tuning
hyperparameter-search
distributed-training
ml-infrastructure
ml-platform
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Jul 15, 2021 - Python
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Updated
Jul 14, 2021 - Python
coder46
commented
Feb 7, 2021
Currently you can only do training when you've committed and pushed all new changes in your branch. This introduces a blocker when a Data Scientist is trying out lots of different changes in their code.
Allow for training even with uncommitted changes. This can be done by taking a git diff of the current branch, storing it and then doing an git apply to the current branch during training
Open-Source Machine Learning Platform
aws
machine-learning
machine-learning-platform
sagemaker
aws-sagemaker
continuous-training
ml-platform
cd4ml
open-source-ml-platform
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Updated
May 28, 2021 - Go
Arup Dutta - Portfolio
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Updated
Aug 26, 2020
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It is neat to have a Colab integration to bentoml docs instead of embeded links