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.
updated at Nov. 10, 2024, 2:13 a.m.
Using deep stacked residual bidirectional LSTM cells (RNN) with TensorFlow, we do Human Activity Recognition (HAR). Classifying the type of movement amongst 6 categories or 18 categories on 2 different datasets.
updated at Oct. 29, 2024, 1:35 a.m.
Simplified interface for TensorFlow (mimicking Scikit Learn) for Deep Learning
updated at Sept. 29, 2024, 3:17 p.m.
Auto-optimizing a neural net (and its architecture) on the CIFAR-100 dataset. Could be easily transferred to another dataset or another classification task.
updated at Feb. 29, 2024, 5:11 a.m.
Using a U-Net for image segmentation, blending predicted patches smoothly is a must to please the human eye.
updated at Aug. 25, 2017, 8:33 p.m.