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Paper_annotations Alternatives
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
paper_annotations reviews and mentions
- Wood Trim Problem (Help Needed)
- Beginning to read ML papers - pathway/general advice
- What is the top paper that one must absolutely read in their deep learning roadmap?
- Keeping up
- How to read more research papers? (tips & tools given)
- Does anyone know a good source for learning the basics of ML? (beginner)
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Annotated Papers: RoBERTa and Few Shot NER
These along with other papers can be found at: https://github.com/au1206/paper_annotations and https://au1206.github.io/
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Annotated Papers: The EfficientNet Family (v1 and v2)
Read along with these easy to follow annotated papers: EfficientNet-V1: https://au1206.github.io/annotated%20paper/EfficientNet/ EfficientNet-V2: https://au1206.github.io/annotated%20paper/EfficientNet-v2/ Github Repo: https://github.com/au1206/paper_annotations
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Fine-Tune BERT for Text Classification with TensorFlow Tutorial
I will also often post annotated papers, where I will try to annotate a recent paper and try to make it more readable for a better understanding for the people just starting out. You can find some at https://au1206.github.io/ and will now consciously try to make it easier to understand.
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Annotated Paper: MLP-Mixer An all MLP Architecture for Vision
Paper Complexity: Easy-Medium Annotated paper link: https://au1206.github.io/annotated%20paper/mlp_mixer/ Github Link: https://github.com/au1206/paper_annotations/blob/master/mlp_mixer.pdf
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au1206/paper_annotations is an open source project licensed under MIT License which is an OSI approved license.
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