sjchoi86/Tensorflow-101 排名第 8,498，此处有 8 个同类条目；NeuronDance/DeepRL 排名第 8,504。

Tensorflow Tutorials using Jupyter Notebook TensorFlow tutorials written in Python (of course) with Jupyter Notebook. Tried to explain as kindly as possible, as these tutorials are intended for TensorFlow beginners. Hope these tutorials to be a useful recipe book for your deep learning projects. Basics of TensorFlow / MNIST / Numpy / Image Processing / Generating Custom Dataset 2. Machine Learing Basics with TensorFlow: Linear Regression / Logistic Regression with MNIST / Logistic Regression with Custom Dataset 3. Multi-Layer Perceptron (MLP): Simple MNIST / Deeper MNIST

/ Xavier Init MNIST / Custom Dataset 4. Convolutional Neural Network (CNN): Simple MNIST / Deeper MNIST / Simple Custom Dataset / Basic Custom Dataset 5. Using Pre-trained Model (VGG): Simple Usage / CNN Fine-tuning on Custom Dataset 6. Recurrent Neural Network (RNN): Simple MNIST / Char-RNN Train / Char-RNN Sample / Hangul-RNN Train / Hangul-RNN Sample 7. Word Embedding (Word2Vec): Simple Version / Complex Version 8. Auto-Encoder Model: Simple Auto-Encoder / Denoising Auto-Encoder / Convolutional Auto-Encoder (deconvolution) 9. Class Activation Map (CAM

): Global Average Pooling on MNIST 10. TensorBoard Usage: Linear Regression / MLP / CNN 11. Face detection with OpenCV Requirements TensorFlow Numpy SciPy Pillow BeautifulSoup Pretrained VGG: inside 'data/' folder Note Most of the codes are simple refactorings of Aymeric Damien's Tutorial or Nathan Lintz's Tutorial.