This is suite of the hands-on training materials that shows how to scale CV, NLP, time-series forecasting workloads with Ray.
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Updated
Feb 13, 2024 - Jupyter Notebook
This is suite of the hands-on training materials that shows how to scale CV, NLP, time-series forecasting workloads with Ray.
Numerically Solving Parametric Families of High-Dimensional Kolmogorov Partial Differential Equations via Deep Learning (NeurIPS 2020)
Hyperparameter tuning for FCN using Ray Tune
Official Repository for the paper: Distributing Deep Learning Hyperparameter Tuning for 3D Medical Image Segmentation
A convenient way to trigger synchronizations to wandb / Weights & Biases if your compute nodes don't have internet!
The project implements the Snake game as an OpenAI Gym environment. Deep learning is implemented using the RLlib library. A convolutional neural network is used to work with the game frames.
1st place solution to Automated Machine Learning https://www.automl.ai/competitions/2
Instance segmentation with U-Net/Mask R-CNN workflow using Keras & Ray Tune
Learning ReLU networks to high uniform accuracy is intractable (ICLR 2023)
Distributing Deep Learning Hyperparameter Tuning for 3D Medical Image Segmentation
Classifying Underlying Placental Issues in Premature Infants with Deep Learning
YOLOV8 - Object detection
DeepAR implementation for seasonal influenza cases in German districts
Low-code machine learning and deep learning
Code to reproduce 'Learning Distance Estimators from Pivoted Embeddings of Metric Objects'.
Build CIFAR10 classifiers using Tensorflow, PyTorch, PyTorch Lightning
Training ReLU networks to high uniform accuracy is intractable
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