72 lines
6.9 KiB
Markdown
72 lines
6.9 KiB
Markdown
# Colab notebooks
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---
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## Quick Start
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- **TensorFlow 1.15 Quickstart**
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[Run in Google Colab](https://colab.research.google.com/github/intel-analytics/analytics-zoo/blob/master/docs/docs/colab-notebook/orca/quickstart/tf_lenet_mnist.ipynb) [View source on GitHub](https://github.com/intel-analytics/analytics-zoo/blob/master/docs/docs/colab-notebook/orca/quickstart/tf_lenet_mnist.ipynb)
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- **Keras 2.3 Quickstart**
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[Run in Google Colab](https://colab.research.google.com/github/intel-analytics/analytics-zoo/blob/master/docs/docs/colab-notebook/orca/quickstart/keras_lenet_mnist.ipynb) [View source on GitHub](https://github.com/intel-analytics/analytics-zoo/blob/master/docs/docs/colab-notebook/orca/quickstart/keras_lenet_mnist.ipynb)
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- **TensorFlow 2 Quickstart**
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[Run in Google Colab](https://colab.research.google.com/github/intel-analytics/analytics-zoo/blob/master/docs/docs/colab-notebook/orca/quickstart/tf2_keras_lenet_mnist.ipynb) [View source on GitHub](https://github.com/intel-analytics/analytics-zoo/blob/master/docs/docs/colab-notebook/orca/quickstart/tf2_keras_lenet_mnist.ipynb)
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- **PyTorch Quickstart**
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[Run in Google Colab](https://colab.research.google.com/github/intel-analytics/analytics-zoo/blob/master/docs/docs/colab-notebook/orca/quickstart/pytorch_lenet_mnist.ipynb) [View source on GitHub](https://github.com/intel-analytics/analytics-zoo/blob/master/docs/docs/colab-notebook/orca/quickstart/pytorch_lenet_mnist.ipynb)
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## Common Use Case
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- **Use `torch.distributed` in Orca**
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[Run in Google Colab](https://colab.research.google.com/github/intel-analytics/analytics-zoo/blob/master/docs/docs/colab-notebook/orca/quickstart/pytorch_distributed_lenet_mnist.ipynb) [View source on GitHub](https://github.com/intel-analytics/analytics-zoo/blob/master/docs/docs/colab-notebook/orca/quickstart/pytorch_distributed_lenet_mnist.ipynb)
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- **Use Spark Dataframe for Deep Learning**
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[Run in Google Colab](https://colab.research.google.com/github/intel-analytics/analytics-zoo/blob/master/docs/docs/colab-notebook/orca/quickstart/ncf_dataframe.ipynb) [View source on GitHub](https://github.com/intel-analytics/analytics-zoo/blob/master/docs/docs/colab-notebook/orca/quickstart/ncf_dataframe.ipynb)
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- **Use Distributed Pandas for Deep Learning**
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[Run in Google Colab](https://colab.research.google.com/github/intel-analytics/analytics-zoo/blob/master/docs/docs/colab-notebook/orca/quickstart/ncf_xshards_pandas.ipynb) [View source on GitHub](https://github.com/intel-analytics/analytics-zoo/blob/master/docs/docs/colab-notebook/orca/quickstart/ncf_xshards_pandas.ipynb)
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- **Use AutoML for Time-Series Forecasting**
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[Run in Google Colab](https://colab.research.google.com/github/intel-analytics/analytics-zoo/blob/master/docs/docs/colab-notebook/chronos/chronos_autots_nyc_taxi.ipynb) [View source on GitHub](https://github.com/intel-analytics/analytics-zoo/blob/master/docs/docs/colab-notebook/chronos/chronos_autots_nyc_taxi.ipynb)
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- **Use TSDataset and Forecaster for Time-Series Forecasting**
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[Run in Google Colab](https://colab.research.google.com/github/intel-analytics/analytics-zoo/blob/master/docs/docs/colab-notebook/chronos/chronos_nyc_taxi_tsdataset_forecaster.ipynb) [View source on GitHub](https://github.com/intel-analytics/analytics-zoo/blob/master/docs/docs/colab-notebook/chronos/chronos_nyc_taxi_tsdataset_forecaster.ipynb)
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- **Use Anomaly Detector for Unsupervised Anomaly Detection**
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[Run in Google Colab](https://colab.research.google.com/github/intel-analytics/analytics-zoo/blob/master/docs/docs/colab-notebook/chronos/chronos_minn_traffic_anomaly_detector.ipynb) [View source on GitHub](https://github.com/intel-analytics/analytics-zoo/blob/master/docs/docs/colab-notebook/chronos/chronos_minn_traffic_anomaly_detector.ipynb)
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- **Enable AutoML for PyTorch**
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[Run in Google Colab](https://colab.research.google.com/github/intel-analytics/analytics-zoo/blob/master/docs/docs/colab-notebook/orca/quickstart/autoestimator_pytorch_lenet_mnist.ipynb) [View source on GitHub](https://github.com/intel-analytics/analytics-zoo/blob/master/docs/docs/colab-notebook/orca/quickstart/autoestimator_pytorch_lenet_mnist.ipynb)
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- **Use AutoXGBoost to auto-tune XGBoost parameters**
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[Run in Google Colab](https://colab.research.google.com/github/intel-analytics/analytics-zoo/blob/master/docs/docs/colab-notebook/orca/quickstart/autoxgboost_regressor_sklearn_boston.ipynb) [View source on GitHub](https://github.com/intel-analytics/analytics-zoo/blob/master/docs/docs/colab-notebook/orca/quickstart/autoxgboost_regressor_sklearn_boston.ipynb)
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## AI Application Case
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- **Use Pytorch for Fashion MNIST Image Classification**
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[Run in Google Colab](https://colab.research.google.com/github/intel-analytics/analytics-zoo/blob/master/docs/docs/colab-notebook/orca/examples/fashion_mnist_bigdl.ipynb) [View source on GitHub](https://github.com/intel-analytics/analytics-zoo/blob/master/docs/docs/colab-notebook/orca/examples/fashion_mnist_bigdl.ipynb)
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- **Use Keras for Text Classification**
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[Run in Google Colab](https://colab.research.google.com/github/intel-analytics/analytics-zoo/blob/master/docs/docs/colab-notebook/orca/examples/basic_text_classification.ipynb) [View source on GitHub](https://github.com/intel-analytics/analytics-zoo/blob/master/docs/docs/colab-notebook/orca/examples/basic_text_classification.ipynb)
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- **Use Pytorch for Image Super Resolution**
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[Run in Google Colab](https://colab.research.google.com/github/intel-analytics/analytics-zoo/blob/master/docs/docs/colab-notebook/orca/examples/super_resolution.ipynb) [View source on GitHub](https://github.com/intel-analytics/analytics-zoo/blob/master/docs/docs/colab-notebook/orca/examples/super_resolution.ipynb)
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