#Lstm-neural-networks
Showing 47 of 47 repositories tagged #lstm-neural-networks, ranked by stars
List of papers, code and experiments using deep learning for time series forecasting
pytorch-kaldi is a project for developing state-of-the-art DNN/RNN hybrid speech recognition systems. The DNN part is managed by pytorch, while feature extraction, label computation, and decoding are performed with the kaldi toolkit.
Stock Price Prediction using Machine Learning Techniques
Introducing neural networks to predict stock prices
Example of Multiple Multivariate Time Series Prediction with LSTM Recurrent Neural Networks in Python with Keras.
Predicting stock prices using a TensorFlow LSTM (long short-term memory) neural network for times series forecasting
OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network
Implementation of a hierarchical CNN based model to detect Big Five personality traits
EQTransformer, a python package for earthquake signal detection and phase picking using AI.
GARCH and Multivariate LSTM forecasting models for Bitcoin realized volatility with potential applications in crypto options trading, hedging, portfolio management, and risk management
A curated list of dedicated resources and applications
Time Series Analysis and Forecasting in Python
Aulas da Escola de Inteligência Artificial de São Paulo
A tensorflow.keras generative neural network for de novo drug design, first-authored in Nature Machine Intelligence while working at AstraZeneca.
Abnormal Event Detection in Videos using SpatioTemporal AutoEncoder
Generate monophonic melodies with machine learning using a basic LSTM RNN
First Version.. Cryptocurrency Prediction with Artificial Intelligence (Deep Learning via LSTM Neural Networks)- Emirhan BULUT
[DEPRECATED] A Neural Network based generative model for captioning images using Tensorflow
This is a project implementing Computer Vision and Deep Learning concepts to detect drowsiness of a driver and sound an alarm if drowsy.
Projects from the Deep Learning Specialization from deeplearning.ai provided by Coursera
This project is about predicting stock prices with more accuracy using LSTM algorithm. For this project we have fetched real-time data from yfinance library.
Drug-Drug Interaction Prediction Based on Knowledge Graph Embeddings and Convolutional-LSTM Network
A recurrent (LSTM) neural network in C
Detecting Sarcasm on Twitter using both traditonal machine learning and deep learning techniques.
A Chrome Extension that promotes politically diverse news reading with Artificial Intelligence!
Classifying the physical activities performed by a user based on accelerometer and gyroscope sensor data collected by a smartphone in the user’s pocket. The activities to be classified are: Standing, Sitting, Stairsup, StairsDown, Walking and Cycling.
Multiple Object Tracking System in Keras + (Detection Network - YOLO)
Python package for Granger causality test with nonlinear forecasting methods.
Electric load forecast using Long-Short-Term-Memory (LSTM) recurrent neural network
This was my Master's project where i was involved using a dataset from Wireless Sensor Data Mining Lab (WISDM) to build a machine learning model to predict basic human activities using a smartphone accelerometer, Using Tensorflow framework, recurrent neural nets and multiple stacks of Long-short-term memory units(LSTM) for building a deep network. After the model was trained, it was saved and exported to an android application and the predictions were made using the model and the interface to speak out the results using text-to-speech API.
Time Series Analysis using LSTM for Wind Energy Prediction.
This repository is the result of our work for the course CSCI-SHU 360 Machine Learning
Automatic trading bot (WIP)
Google TensorFlow Developer Certificate Study Guide
Image Captioning: Implementing the Neural Image Caption Generator with python
Paratope Prediction using Deep Learning
Predict the toxicity rating of comment made by the user.
A deep learning project for automated chorus detection in songs, featuring a command-line interface (CLI) tool that allows users to input a YouTube link and utilize a pre-trained CRNN model to detect chorus sections from a song on YouTube
Corpus and a baseline neural network system for Named Entity Recognition in Hindi-English Code-Mixed social media text.
High Frequency Trading strategies.
Stock Price Prediction using LSTM
Deep Learning-based chatbot using Tensorflow
Ensemble framework of some log based anomaly detection work.
🌍 Welcome to the Earthquake Prediction Analysis Project! 🚀 This project aims to predict earthquake magnitudes using LSTM neural networks and analyze seismic data. Explore, analyze, and forecast earthquakes with ease! 📈🔮
Single-stock analysis using Python and local machine learning/ AI tools (Ollama, LSTM).
Sensor data of a renowned power plant has given by a reliable source to forecast some feature. Initially the work has done with KNIME software. Now the goal is to do the prediction/forecasting with machine learning. The idea is to check the result of forecast with univariate and multivariate time series data. Regression method, Statistical method.
In this project, I have tried to predict the stock price of Microsoft using LSTM