rnns

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

Dilated RNNs in pytorch

e3d-lstm; Eidetic 3D LSTM A Model for Video Prediction and Beyond

Handwriting Synthesis and Prediction - PyTorch Implementation

This repository contains my solutions to the assignments for Stanford's CS231n "Convolutional Neural Networks for Visual Recognition" (Spring 2020).

Deep Recurrent Neural Networks (RNNs) for Time-Series Prediction

AI@UCF's custom-made course, organized by semesters

This repository is for the Session held in International Conference on Data Management, Analytics and Innovation, New Delhi 2020

RNNs in the view of dynamical systems

Generating Seinfeld TV scripts using RNNs

A seq2seq model trained on dialogue.

Udacity's Deep-Learning Nano-degree's TV Script Generation Project.

A simple series of programs to train gated recurrent neural networks with PyTorch and generate text based on them.

Code for submission of Speiser et al to spike-finder-challenge 2017

Generation of tv scripts using rnn's of simpsons tv show.

Understand the learning process of RNNs and discover the LSTM network architecture. Solve problems and perform Natural Language Processing using sequences of data

A PyTorch implementation of CNNs and RNNs on MNIST handwritten digits.

Repository implementing Learnable Gradient Descent method for image restoration via recurrent neural networks (RNNs)

Natural Language Processing (NLP) based and trained on RNNs(LSTM) will be powerful enough to generate a fake TV script on Seinfield American TV series. Building a Seinfeld TV scripts AI generator using RNNs.

CS224n : Natural Language Processing with Deep Learning Assignments, Winter 2017, Stanford University.

Projects from deeplearning.ai's course hosted on Coursera

Essays on the Political Economy of the American Frontier

Example project of LSTM in Keras for google stocks prediction.

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.

Deliverables and Implementations from Andrew Ng's Coursera Specialization, deeplearning.ai

Explores language production using recurrent neural networks and distributed semantic representations.

Learn the concepts and applications of RNNs (specifically, Long Short-Term Method networks) and implement these architectures to build sequential models to predict results

Predicting missing metadata with recurrent neural network (RNNs) based entity extraction

This Repository is the work of Deep learning Project as part of MLDM M2 Masters in University Jean Monnet

Mathematical Implementation of RNNs from scratch using just numpy