modulabs/modu-tensorflow

modu-tensorflow

모두연 풀잎스쿨 "Flow me to the moon" 에서 활동하는 연구원들이 정리한 내용입니다. 아래의 참고자료를 기반으로 작성하고 있습니다.

• CS 20: Tensorflow for Deep Learning Research

  • Syllabus : http://web.stanford.edu/class/cs20si/syllabus.html
  • Repository : https://github.com/chiphuyen/stanford-tensorflow-tutorials

• Tensorflow tutorials

  • Simple Audio Recognition, Recurrent Neural Networks, Seq2Seq with Attention
  • Link : https://www.tensorflow.org/tutorials/

• Models and examples built with TensorFlow

  • Inception, slim, Show and Tell
  • Repository : https://github.com/tensorflow/models/research

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Week01

• Overview and Operations
  • 01_hello_TF.ipynb
  • 02_TF_eager.ipynb
  • 03_tensorboard.ipynb
  • 04_TF_dimension.ipynb
  • 05_tf.Variable.ipynb
  • 06_tf.placeholder.ipynb

Week02

• Linear Regression
  • 01_linear_regression.ipynb
  • 02_linear_regression_with_batch.ipynb
  • 03_linear_regression_with_batch_tf.losses.ipynb
• tf.data
  • 05_tf.data.ipynb
• Logistic Regression
  • 06_logistic_regression.ipynb
  • 07_logistic_regression_with_tf.data.ipynb
• Variable sharing and managing experiments

Week03

• Introduction to ConvNet
• ConvNet in TensorFlow
  • 01_mnist_cnn_with_tf.layers.ipynb
  • 02_mnist_cnn_with_slim.ipynb
  • 03_tf.train.Saver.save.ipynb
  • 04_tf.train.Saver.restore.ipynb
  • 05_mnist_cnn_with_train_validation_split.ipynb
  • 06_mnist_cnn_with_batch_norm_and_regularizer.ipynb

Week04

• Models : Inception and slim
  • 01_vgg_slim.ipynb
  • 02_tfrecords.ipynb
  • 03_transfer_learning_inception_v3.ipynb

Week05

• Style Transfer
  • 01_style_transfer.ipynb
  • 02_style_transfer.ipynb

Week06

• Generative Model
  • Generative Adversarial Networks
    • 01_dcgan.ipynb
    • 02_cgan.ipynb
  • Variational Auto-Encoder

Week07

• Recurrent Neural Networks
  • 01_many_to_one_classification.ipynb
  • 02_many_to_many_classification.ipynb

Week08

• Seq2Seq with Attention
  • 01_seq2seq.ipynb
  • 02_seq2seq_with_attention.ipynb

Week09

• Model : Show and Tell

Week10

• Model : Pix2Pix
  • pix2pix.ipynb