In this tutorial, we will build a TensorFlow RNN model for Time Series Prediction.
Build a basic seq2seq model in TensorFlow for chatbot application.
Build machine translation seq2seq or encoder-decoder model in TensorFlow.
The sequence to Sequence model is used for a whole bunch of different stuff everything from chatbots to speech to text to dialogue systems to Q&A to image captioning.
TensorFlow provides a high-level API that makes it easy to build a neural network.
When you use RNN cell this defines all the weights and biases that we had internally,
Rather than doing one-hot encoding, we tend to represent words with shorter vectors which can have continuous values.it’s called an embedding.
One of the key ideas of word embeddings is a way of representing words that model automatically understand analogies like that “Man is the Woman as King is the Queen”.
TensorFlow Object Detection API to get image feature maps and a convolutional layer to find bounding boxes for recognized objects.
With TensorFlow Hub, you can build, share and reuse pieces of machine learning.
