- A Rant on Kaggle Competition Code (and Most Research Code) https://www.neuraxio.com/en/blog/clean-code/2019/12/26/machine-learning-competition-code.html 3 comments deeplearning
- A Rant on Kaggle Competition Code (and Most Research Code) https://www.neuraxio.com/en/blog/clean-code/2019/12/26/machine-learning-competition-code.html 11 comments datascience
Linking pages
- Some Reasons Why Deep Learning has a Bright Future – Neuraxio https://www.neuraxio.com/en/blog/deep-learning/2019/12/29/why-deep-learning-has-a-bright-future.html 0 comments
- GitHub - guillaume-chevalier/seq2seq-signal-prediction: Signal forecasting with a Sequence-to-Sequence (seq2seq) Recurrent Neural Network (RNN) model in TensorFlow - Guillaume Chevalier https://github.com/guillaume-chevalier/seq2seq-signal-prediction 0 comments
Linked pages
- GitHub - facebookresearch/fastText: Library for fast text representation and classification. https://github.com/facebookresearch/fastText 53 comments
- GitHub - google-research/bert: TensorFlow code and pre-trained models for BERT https://github.com/google-research/bert 21 comments
- GitHub - Neuraxio/Neuraxle: The world's cleanest AutoML library ✨ - Do hyperparameter tuning with the right pipeline abstractions to write clean deep learning production pipelines. Let your pipeline steps have hyperparameter spaces. Design steps in your pipeline like components. Compatible with Scikit-Learn, TensorFlow, and most other libraries, frameworks and MLOps environments. https://github.com/Neuraxio/Neuraxle 0 comments
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