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RNN architectures trained with Backpropagation and Reservoir Computing (RC) methods for forecasting high-dimensional chaotic dynamical systems.
A data-driven method to calculate the Lyapunov exponent of a dynamical system employing a GRU-RNN.
Deep Learning notes and practical implementation with Tensorflow and keras. Text Analytics and practical application implementation with NLTK, Spacy and Gensim.
Weather forecasting using recurrent neural network
The final project for ECE C147/C247, which evaluates the performance of CNN + Transformer and CNN + GRU + SimpleRNN models on an EEG dataset.
Multiclass Multilabel prediction for stack overflow Questions using NLP
Trigger word detection is the technology that allows devices like Amazon Alexa, Google Home, Apple Siri, and Baidu DuerOS to wake up upon hearing a certain word
Code and data for the NLLP 2021 paper: `Multi-granular Legal topic Classification on Greek Legislation`
Siamese Manhattan Bi-GRU for semantic similarity between sentences
:robot: :capital_abcd: Making the vaccine sentiment classifier using tweets as datasets with the help of Pytorch Neural Networks and Glove word embeddings. Using both feed-forward nets and bidirectional stacked RNNs.
Collection of my Deep Learning and Machine Learning notebooks.
An attempt to collect and use data to find a player's "Patterns of Play". These can be exploited in a match.
Gated Recurrent Units (GRUs) are a type of RNN designed to capture long-term dependencies in sequential data
My repo of assignments for the AUEB M.Sc. in Data Science (2018-2020)
Used RNN architectures to classify the respiratory sound samples into four different categories. This will in turn help detect respiratory diseases in patients.
Seq2Seq model that restores punctuation on English input text.
Comparison between RNNs and Attention in Document Classification
Recurrent neural network with GRUs for trigger word detection from an audio clip
GRU-Gated Attention Model Implementation in order to train it to translate over Cap-verdian criole to English.
Stock price prediction using LSTM, GRU and LSTM + GRU (base on VNINDEX)
Generate Captions for images using Encoder, Decoder model.
Music Generation using Multi-Layer Gradient Recurrent Units. This involves using many-to-many type of RNN for input-output mapping.
IN5400 Mandatory exercise 2
Sentence Autocompletion Project with GRU based RNN using Alice in Wonderland text dataset and NYT comments dataset
Recurrent Neural Networks (RNNs) to classify Stack Overflow posts using PyTorch
Kaggle Competition
Develop a Recurrent Neural Network (RNN) that can learn the lyrics and melodies of songs
A machine learning project for detecting hand gestures for Smart TVs using CNN and RNN
Experiment for understanding RNN architecture
This is a very brief notebook on NLP, it contains a "Disaster Analysis" project in which all the possible architectures were shown and described briefly.
Introduction to Neural Quantum States
A deep learning project for Time Series Forecasting of bike count by using Recurrent Neural Networks and UCI Bike Sharing Dataset.