# tfjs-examples **Repository Path**: edencfc/tfjs-examples ## Basic Information - **Project Name**: tfjs-examples - **Description**: Examples built with TensorFlow.js 镜像加速 - **Primary Language**: Python - **License**: Apache-2.0 - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2019-07-15 - **Last Updated**: 2020-12-16 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README # TensorFlow.js Examples This repository contains a set of examples implemented in [TensorFlow.js](http://js.tensorflow.org). Each example directory is standalone so the directory can be copied to another project. # Overview of Examples
Example name | Demo link | Input data type | Task type | Model type | Training | Inference | API type | Save-load operations |
---|---|---|---|---|---|---|---|---|
abalone-node | Numeric | Loading data from local file and training in Node.js | Multilayer perceptron | Node.js | Node.js | Layers | Saving to filesystem and loading in Node.js | |
addition-rnn | 🔗 | Text | Sequence-to-sequence | RNN: SimpleRNN, GRU and LSTM | Browser | Browser | Layers | |
addition-rnn-webworker | Text | Sequence-to-sequence | RNN: SimpleRNN, GRU and LSTM | Browser: Web Worker | Browser: Web Worker | Layers | ||
baseball-node | Numeric | Multiclass classification | Multilayer perceptron | Node.js | Node.js | Layers | ||
boston-housing | 🔗 | Numeric | Regression | Multilayer perceptron | Browser | Browser | Layers | |
cart-pole | 🔗 | Reinforcement learning | Policy gradient | Browser | Browser | Layers | IndexedDB | |
chrome-extension | Image | (Deploying TF.js in Chrome extension) | Convnet | Browser | ||||
custom-layer | 🔗 | (Defining a custom Layer subtype) | Browser | Layers | ||||
data-csv | 🔗 | Building a tf.data.Dataset from a remote CSV | ||||||
data-generator | 🔗 | Building a tf.data.Dataset using a generator | Regression | Browser | Browser | Layers | ||
date-conversion-attention | 🔗 | Text | Text-to-text conversion | Attention mechanism, RNN | Node.js | Browser and Node.js | Layers | Saving to filesystem and loading in browser |
electron | Image | (Deploying TF.js in Electron-based desktop apps) | Convnet | Node.js | ||||
fashion-mnist-vae | Image | Generative | Variational autoencoder (VAE) | Node.js | Browser | Layers | Export trained model from tfjs-node and load it in browser | |
iris | 🔗 | Numeric | Multiclass classification | Multilayer perceptron | Browser | Browser | Layers | |
iris-fitDataset | 🔗 | Numeric | Multiclass classification | Multilayer perceptron | Browser | Browser | Layers | |
jena-weather | 🔗 | Sequence | Sequence-to-prediction | MLP and RNNs | Browser and Node | Browser | Layers | |
lstm-text-generation | 🔗 | Text | Sequence prediction | RNN: LSTM | Browser | Browser | Layers | IndexedDB |
mnist | 🔗 | Image | Multiclass classification | Convolutional neural network | Browser | Browser | Layers | |
mnist-acgan | 🔗 | Image | Generative Adversarial Network (GAN) | Convolutional neural network; GAN | Node.js | Browser | Layers | Saving to filesystem from Node.js and loading it in the browser |
mnist-core | 🔗 | Image | Multiclass classification | Convolutional neural network | Browser | Browser | Core (Ops) | |
mnist-node | Image | Multiclass classification | Convolutional neural network | Node.js | Node.js | Layers | Saving to filesystem | |
mnist-transfer-cnn | 🔗 | Image | Multiclass classification (transfer learning) | Convolutional neural network | Browser | Browser | Layers | Loading pretrained model |
mobilenet | 🔗 | Image | Multiclass classification | Convolutional neural network | Browser | Layers | Loading pretrained model | |
polynomial-regression | 🔗 | Numeric | Regression | Shallow neural network | Browser | Browser | Layers | |
polynomial-regression-core | 🔗 | Numeric | Regression | Shallow neural network | Browser | Browser | Core (Ops) | |
quantization | Various | Demonstrates the effect of post-training weight quantization | Various | Node.js | Node.js | Layers | ||
sentiment | 🔗 | Text | Sequence-to-binary-prediction | LSTM, 1D convnet | Node.js or Python | Browser | Layers | Load model from Keras and tfjs-node |
simple-object-detection | 🔗 | Image | Object detection | Convolutional neural network (transfer learning) | Node.js | Browser | Layers | Export trained model from tfjs-node and load it in browser |
snake-dqn | 🔗 | Reinforcement learning | Deep Q-Network (DQN) | Node.js | Browser | Layers | Export trained model from tfjs-node and load it in browser | |
translation | 🔗 | Text | Sequence-to-sequence | LSTM encoder and decoder | Node.js or Python | Browser | Layers | Load model converted from Keras |
tsne-mnist-canvas | Dimension reduction and data visualization | tSNE | Browser | Browser | Core (Ops) | |||
webcam-transfer-learning | 🔗 | Image | Multiclass classification (transfer learning) | Convolutional neural network | Browser | Browser | Layers | Loading pretrained model |
website-phishing | 🔗 | Numeric | Binary classification | Multilayer perceptron | Browser | Browser | Layers |