deshpandenu / Time-Series-Forecasting-of-Amazon-Stock-Prices-using-Neural-Networks-LSTM-and-GAN-
Project analyzes Amazon Stock data using Python. Feature Extraction is performed and ARIMA and Fourier series models are made. LSTM is used with multiple features to predict stock prices and then sentimental analysis is performed using news and reddit sentiments. GANs are used to predict stock data too where Amazon data is taken from an API as …
☆399Updated 4 years ago
Related projects ⓘ
Alternatives and complementary repositories for Time-Series-Forecasting-of-Amazon-Stock-Prices-using-Neural-Networks-LSTM-and-GAN-
- In this project, we will compare two algorithms for stock prediction. First, we will utilize the Long Short Term Memory(LSTM) network to …☆225Updated 3 years ago
- This project seeks to utilize Deep Learning models, Long-Short Term Memory (LSTM) Neural Networks to predict stock prices.☆83Updated 3 years ago
- Stanford Project: Artificial Intelligence is changing virtually every aspect of our lives. Today’s algorithms accomplish tasks that until…☆253Updated last year
- kennedyCzar / STOCK-RETURN-PREDICTION-USING-KNN-SVM-GUASSIAN-PROCESS-ADABOOST-TREE-REGRESSION-AND-QDAForecast stock prices using machine learning approach. A time series analysis. Employ the Use of Predictive Modeling in Machine Learning …☆127Updated 2 years ago
- Applied an ARIMA-LSTM hybrid model to predict future price correlation coefficients of two assets☆396Updated 6 years ago
- ☆76Updated 4 years ago
- Forecasting directional movements of stock prices for intraday trading using LSTM and random forest☆417Updated 3 years ago
- Stock Price Prediction using CNN-LSTM☆83Updated 4 years ago
- Introduction to time series preprocessing and forecasting in Python using AR, MA, ARMA, ARIMA, SARIMA and Prophet model with forecast eva…☆319Updated 5 years ago
- Programs for stock prediction and evaluation☆350Updated 2 years ago
- ☆53Updated 5 years ago
- Comparative Analysis of Conv1D-LSTM with CNN , LSTM for Stock Price Prediction☆60Updated 6 years ago
- Attention-based CNN-LSTM and XGBoost hybrid model for stock prediction☆279Updated 2 years ago
- ☆78Updated 2 years ago
- By combining GARCH(1,1) and LSTM model implementing predictions.☆54Updated 5 years ago
- Implementing a Generative Adversarial Network on the Stock Market☆120Updated 2 years ago
- This project seeks to utilize Deep Learning models, Long-Short Term Memory (LSTM) Neural Network algorithm, to predict stock prices.☆296Updated 4 years ago
- In this project, we implement and compare the performance of several machine learning and deep learning algorithms in predicting the US s…☆49Updated 3 years ago
- LSTM-XGBoost Time Series Forecasting☆108Updated 9 months ago
- Technical and sentiment analysis to predict the stock market with machine learning models based on historical time series data and news a…☆149Updated 10 months ago
- OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network☆574Updated last year
- Predicting stock price using historical data of a company, using Neural networks (LSTM).☆153Updated 5 years ago
- Comparing Long Term Short Memory (LSTM) & Gated Re-current Unit (GRU) during forecasting of oil price .Exploring multivariate relationsh…☆43Updated 2 years ago
- BEST SCORE ON KAGGLE SO FAR. Mean Square Error after repeated tuning 0.00032. Used stacked GRU + LSTM layers with optimized architecture,…☆68Updated 6 years ago
- This repository contains a throughout explanation on how to create different deep learning models in Keras for multivariate (tabular) tim…☆140Updated 5 years ago
- Stock Market Prediction Using Unsupervised Features☆328Updated last year
- Hidden Markov Model (HMM) based stock forecasting☆95Updated 6 years ago
- Machine learning models for time series analysis☆370Updated 3 years ago