tfjs-examples | Examples built with TensorFlow.js | Machine Learning library

tfjs-examples is a JavaScript library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow applications. tfjs-examples has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. You can download it from GitHub.

Loading data from local file and training in Node.js. Saving to filesystem and loading in Node.js. RNN: SimpleRNN, GRU and LSTM. RNN: SimpleRNN, GRU and LSTM. (Deploying TF.js in Chrome extension). (Defining a custom Layer subtype). Building a tf.data.Dataset from a remote CSV. Building a tf.data.Dataset using a generator. Saving to filesystem and loading in browser. (Deploying TF.js in Electron-based desktop apps). Export trained model from tfjs-node and load it in browser. Multiclass classification, object detection, segmentation. Generative Adversarial Network (GAN). Convolutional neural network; GAN. Saving to filesystem from Node.js and loading it in the browser. Multiclass classification (transfer learning). Demonstrates the effect of post-training weight quantization. Load model from Keras and tfjs-node. Convolutional neural network (transfer learning). Export trained model from tfjs-node and load it in browser. Export trained model from tfjs-node and load it in browser. LSTM encoder and decoder. Load model converted from Keras. Dimension reduction and data visualization. Multiclass classification (transfer learning).