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Stock Market Prediction Web App based on Machine Learning and Sentiment Analysis of Tweets (API keys included in code). The front end of the Web App is based on Flask and Wordpress. The App forecasts stock prices of the next seven days for any given stock under NASDAQ or NSE as input by the user.
- Stock-Prediction-Models
Gathers machine learning and deep learning models for Stock...
- AIAlpha
The workflow is similar to the approach in the excellent...
- Stock-Prediction-Models
In the current era stock price prediction plays a key role for prediction of future data with respect to training the past data by using machine learning or deep learning technologies. Building a model and then passing the past data as input that is as training data to the model based on the results acquired need to consider an algorithm which ...
A machine learning model to predict the selling price of goods to help an entrepreneur understand important pricing factors in the industry. Highly comprehensive analysis with all data cleaning, exploration, visualization, feature selection, model building, evaluation, and assumptions with validity steps explained in detail.
The focus of this project is to forecast the stock price of Reliance Industries Limited (RELIANCE.NS) using the ARIMA model for up to 2 years and to predict the next day's stock price using Random Forest and LSTM to predict stock prices for test data.
16 Αυγ 2023 · This project’s main goal was to develop a predictive model that could forecast stock prices for a given future date. To achieve this, we turned to historical stock data available from Yahoo...
LSTM can quickly process a whole data series and adds a memory cell, which allows the network to link memories and feedback remotely efficiently. In this example we have generated a series of sequences in order to use time steps to predict a given price.
6 Φεβ 2021 · In this work, we propose an approach of hybrid modeling for stock price prediction building different machine learning and deep learning-based models. For the purpose of our study, we have used NIFTY 50 index values of the National Stock Exchange (NSE) of India, during the period December 29, 2014 till July 31, 2020.
