There are 11 repositories under rnn-lstm topic.
Collection of must read papers for Data Science, or Machine Learning / Deep Learning Engineer
Implementation of Logistic Regression, MLP, CNN, RNN & LSTM from scratch in python. Training of deep learning models for image classification, object detection, and sequence processing (including transformers implementation) in TensorFlow.
RNN architectures trained with Backpropagation and Reservoir Computing (RC) methods for forecasting high-dimensional chaotic dynamical systems.
Cuda implementation of Extended Long Short Term Memory (xLSTM) with C++ and PyTorch ports
This project provides implementations with Keras/Tensorflow of some deep learning algorithms for Multivariate Time Series Forecasting: Transformers, Recurrent neural networks (LSTM and GRU), Convolutional neural networks, Multi-layer perceptron
Time Series Analysis of Air Pollutants(PM2.5) using LSTM model
This project is about performing Speaker diarization for Hindi Language.
Deep Learning notes and practical implementation with Tensorflow and keras. Text Analytics and practical application implementation with NLTK, Spacy and Gensim.
Natural Language Processing for Multiclass Classification: A repository containing NLP techniques for multiclass classification of text data.
Monorepo for trading algorithms
Contact: Alexander Hartl, Maximilian Bachl, Fares Meghdouri. Explainability methods and Adversarial Robustness metrics for RNNs for Intrusion Detection Systems. Also contains code for "SparseIDS: Learning Packet Sampling with Reinforcement Learning" (branch "rl").
This repository contains the notebooks used in my project "Air quality analysis and forecasting"
Weather forecasting using recurrent neural network
Beginner Friendly CheatCodes
Fake News Detection Using Recurrent Neural Networks (RNNs) & Long Short Term Memory (LSTM).
Predicting stock market prices using RNN with LSTM
In this project we will be building a model capable of generating notes and chords after learning from the dataset of songs we provide to our recurrent neural network and create songs. Before we start, let us recall few of the basic concepts and terminologies we will be using in this project and add to that knowledge the concepts required to successfully train our model to be an excellent composer.
Deep Learning, Attention, Transformers, BERT, GPT-2, GTP-3
This project contains the file of my undergraduate Final Year Project. This project aims to expose cyberbullying in Twitter by using Machine Learning to classify whether the tweet is suspicious or not. A deployment has been created using streamlit.
Forecasting exchange rates by using commodities prices
"Exploring the Dynamics of Stock Price Prediction: Harnessing the power of LSTM neural networks, this project demonstrates the application of deep learning techniques to forecast Apple's stock prices using historical data from Yahoo Finance."
The main task of the character-level language model is to predict the next character given all previous characters in a sequence of data, i.e. generates text character by character.
Coherent / Meaningful lyrics generation using RNNs , with a dataset created by web-scraping the GENIUS website using its API.
🚀 Leveraging advanced RNN with LSTM for efficient, real-time anomaly detection in IoT networks, optimized for performance in resource-constrained environments.
Time series analysis on NIFTY-50 index stock data. The project visualises trends in stock data and explores various time-series analysis models such as ARIMA, ARMA and deep learning models such as LTSM and RNN to predict stock prices with the highest accuracy.
Deep learning models for classifying ECG time series
This is my first deep learning project in which I implemented a LSTM model on abc notation music data.
Predicting Sick Patient Volume in a Pediatric Outpatient Setting using Time Series Analysis [Presented at MLHC 2019]
Pytorch implementation of a sentence sentiment classification model with CNN, RNN, RNF (Recurrent Neural Filter) and BERT
✨Using RNN and LSTM generate poetry by Keras, and translate poetry. (通过Keras实现基于RNN与LSTM的藏头诗自动生成模型, 并将生成的古诗翻译成英文.)
Generate caption on images using CNN Encoder- LSTM Decoder structure
Algotrading toolkit using customizable strategies, genetic algorithms, and RNN-based strategies
English to Telugu Neural Machine Translation using Encoder-Decoder