EP.2 – Transfer learning : VGG16 Option 200:08:09
EP.3 – Autoencoder00:17:39
EP.4 – Autoencoder : Feature Extraction and Encoder00:08:28
EP.5 – Autoencoder : Reconstructor and Combine Feature00:07:20
EP.6 – Question and Answer00:03:06
EP.7 – Autoencoder : Convolutional Neural Network (CNN), UpSampling 2D and Denoising00:19:37
EP.8 – Semantic Segmentation (SegNet) Batch Normalization00:11:53
EP.9 – Lung Segmentation (SegNet)00:10:52
EP.10 – U-Net and Dropout00:08:44
EP.11 – Question and Answer00:06:25
EP.12 – Residual Neural Network (ResNet)00:15:35
EP.13 – CIFAR – 10 (Datasets)00:12:04
EP.14 – Traditional Generative Adversarial Networks (GANs)00:30:22
EP.15 – Super Resolution GAN (SRGAN)00:29:25
EP.16 – Audio (STFT, MFCC) and Example of Audio Recognition using CNN00:05:31
EP.17 – Time series, Simple NN and Example of Stock Prediction00:03:24
EP.18 – Feature Extraction (Text) : Word2Vec, RNN and LSTM00:19:54
EP.19 – Colab Example : Audio, Time Series and Text00:09:02
EP.20 – Q and A : การประยุกต์ใช้ Signal กับ GANs และ การประยุกต์ใช้ Multi-tail ใน Stock00:04:15