Tensorflow 101 (sjchoi86)
Introduction
Basics of TensorFlow
MNIST
Numpy
Image Processing
Generating Custom Dataset
Machine Learing Basics with TensorFlow
Linear Regression
Logistic Regression with MNIST
Logistic Regression with Custom Dataset
Multi-Layer Perceptron (MLP)
Simple MNIST
Deeper MNIST
Xavier Init MNIST
Custom Dataset
Convolutional Neural Network (CNN)
Simple MNIST
Deeper MNIST
Simple Custom Dataset
Basic Custom Dataset
Using Pre-trained Model (VGG)
Simple Usage
CNN Fine-tuning on Custom Dataset
Recurrent Neural Network (RNN)
Simple MNIST
Char-RNN Train
Char-RNN Sample
Hangul-RNN Train
Hangul-RNN Sample
Word Embedding (Word2Vec)
Simple Version
Complex Version
Auto-Encoder Model
Simple Auto-Encoder
Denoising Auto-Encoder
Convolutional Auto-Encoder (deconvolution)
Class Activation Map (CAM)
Global Average Pooling on MNIST
TensorBoard Usage
Linear Regression
MLP
CNN
Semantic segmentation
Super resolution (in progress)
Web crawler
Gaussian process regression
Neural Style
Face detection with OpenCV
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Class Activation Map (CAM)
Class Activation Map (CAM)
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