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 #### 5 - Data Management
 - **Build an image dataset** ([notebook](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/notebooks/5_DataManagement/build_an_image_dataset.ipynb)) ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/5_DataManagement/build_an_image_dataset.py)). Build your own images dataset with TensorFlow data queues, from image folders or a dataset file.
 - **TensorFlow Dataset API** ([notebook](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/notebooks/5_DataManagement/tensorflow_dataset_api.ipynb)) ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/5_DataManagement/tensorflow_dataset_api.py)). Introducing TensorFlow Dataset API for optimizing the input data pipeline.
+- **Load and Parse data** ([notebook](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/notebooks/5_DataManagement/load_data.ipynb)). Build efficient data pipeline (Numpy arrays, Images, CSV files, custom data, ...).
+- **Build and Load TFRecords** ([notebook](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/notebooks/5_DataManagement/tfrecords.ipynb)). Convert data into TFRecords format, and load them.
+- **Image Transformation (i.e. Image Augmentation)** ([notebook](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/notebooks/5_DataManagement/image_transformation.ipynb)). Apply various image augmentation techniques, to generate distorted images for training.
 
 #### 6 - Multi GPU
 - **Basic Operations on multi-GPU** ([notebook](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/notebooks/6_MultiGPU/multigpu_basics.ipynb)) ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/6_MultiGPU/multigpu_basics.py)). A simple example to introduce multi-GPU in TensorFlow.