Deep Recurrent Neural Networks (RNNs) for Time-Series Prediction
-
Updated
Oct 24, 2017 - Python
Deep Recurrent Neural Networks (RNNs) for Time-Series Prediction
Code for submission of Speiser et al to spike-finder-challenge 2017
Projects from deeplearning.ai's course hosted on Coursera
Recurrent Neural Networks for Text Generator
Deliverables and Implementations from Andrew Ng's Coursera Specialization, deeplearning.ai
CS224n : Natural Language Processing with Deep Learning Assignments, Winter 2017, Stanford University.
Mathematical Implementation of RNNs from scratch using just numpy
Example project of LSTM in Keras for google stocks prediction.
Explores language production using recurrent neural networks and distributed semantic representations.
Handwriting Synthesis and Prediction - PyTorch Implementation
Sentiment analysis and prediction project based on a Recurrent Neural Network Model (RNN) that can read in some text and make a prediction about the sentiment of that text.
Essays on the Political Economy of the American Frontier
This repository is for the Session held in International Conference on Data Management, Analytics and Innovation, New Delhi 2020
Learn the concepts and applications of RNNs (specifically, Long Short-Term Method networks) and implement these architectures to build sequential models to predict results
Understand the learning process of RNNs and discover the LSTM network architecture. Solve problems and perform Natural Language Processing using sequences of data
Udacity's Deep-Learning Nano-degree's TV Script Generation Project.
Generating Seinfeld TV scripts using RNNs
A simple series of programs to train gated recurrent neural networks with PyTorch and generate text based on them.
A lightweight but powerful library to build token indices for NLP tasks, compatible with major Deep Learning frameworks like PyTorch and Tensorflow.
Add a description, image, and links to the rnns topic page so that developers can more easily learn about it.
To associate your repository with the rnns topic, visit your repo's landing page and select "manage topics."