/公众号/
presentations
Week6-2c Generative Adversarial Network.pptx
Week6-2b Adversarial Attack.pptx
Week6-2a Bayesian Optimization.pptx
Week6-1d CNN finetune with VGG (use_vgg
cnn_finetune_vgg).pptx
Week6-1c Neural Style Code.pptx
Week6-1b Neural Style.pptx
Week6-1a Residual Networks and Analysis.pptx
Week5-2c Hangul-RNN.pptx
Week5-2b Image Captioning.pptx
Week5-2a Word2Vec.pptx
Week5-2a Word2Vec again.pptx
Week5-1b Implementing RNN (rnn_mnist_simple).pptx
Week5-1a RNN + LSTM + Handwrting Gen.pptx
Week4-2d Deep reinforcement learning.pptx
Week4-2c Super resolution.pptx
Week4-2b Visual QnA.pptx
Week4-2a RNN (colah blog).pptx
Week4-1c TensorBoard.pptx
Week4-1b Other dections (YOLO
AttentionNet).pptx
Week4-1a Image detection.pptx
Week4-1a Image detection (RCNN
SPPnet
FastRCNN
FasterRCNN).pptx
Week3-2c Denoising deconvolutional network.pptx
Week3-2b Use your own dataset (basic_gendataset
lr
mlp
cnn).pptx
Week3-2a Weakly supervised learning.pptx
Week3-1e Implementing semantic segmentation (semseg_basic).pptx
Week3-1d Powerful CNN (cnn_mnist_basic).pptx
Week3-1c What is CNN (cnn_mnist_simple).pptx
Week3-1b Semantic segmentation details+SOTA.pptx
Week3-1a Semantic segmentation.pptx
Week2-2c Denoising auto-encoder (dae_mnist).pptx
Week2-2b Restricted Boltzmann machine.pptx
Week2-2a Optimizaiton methods.pptx
Week2-1f Regulaziation.pptx
Week2-1e Generate your own dataset (basic_gendataset).pptx
Week2-1d Multi-layer perceptron (mlp_mnist_simple).pptx
Week2-1c AlphaGo.pptx
Week2-1b GoogLeNet.pptx
Week2-1a Week1 summary.pptx
Week1-2d Logistic regression (logistic_regression_mnist).pptx
Week1-2c TensorFlow basic (basic_tensorflow).pptx
Week1-2b CNN and AlexNet.pptx
Week1-2a Terminologies.pptx
Week1-1d MNIST (basic_mnist) and image processing (basic_imgprocess).pptx
Week1-1c Python basic (basic_python).pptx
Week1-1b Deep learning intro.pptx
Week1-1a Class introduction.pptx
Ubuntu in virtualbox.pptx
Notebooks are in tensorflow-101 (github@sjchoi86).rtf