Tuesday, June 26, 2018
Recurrent Neural Network RNN Basics
Recurrent Neural Network (RNN) is useful for processing sequence data like sound, words, and time series data . RNN remembers a bit of the state from before. It can predict what will come next. Time series is good for heart disease over time, hormone level, blood sugar.
RNN weakness: sometimes gradients too close to 0 or too computationally large. It can also be bad at tracking long term memories - need to use LSTM instead, which has a forget gate, input gate, update layer, output layer
Transform sequences like text, music, time series data,
Build a RNN generate new text character by character
Natural language processing, Word embedding, Word2Vec model, Semantic relationship between words,
Combine embedding and RNN to predict sentiment of movie reviews
Upgrade your skills with Codecademy's Pro Intensive, Machine Learning Fundamentals. Each unit will cover conceptual and syntax lessons ...
Google's algorithm has pushed websites to deploy mobile friendly websites, but sometimes business owners and developers really need to a...
The bogus request from P2PU to hunt for HTML tags in real life has yielded a lot of good thoughts. My first impression was that this is stup...
Specialty sauces are also available for retail. Bay Area restaurant menu. Also see pictures of the dishes, restaurant decors below ...