Stock price forecasting stuff with BERT

A Django app to predict realtime stock market prices for NSE India and NYSE using LSTM.

In this repository, the goal is to predict the tick direction of a stock based on its current order book and trade data. A LSTM Neural Network is used as an example of potential solution for such problem.

Implementação de uma LSTM para prever fechamento de ações na B3. Scripts para análise e predição de valores.

Forecasting stock prices with Long Short Term Memory (LSTM) architecture

Backtesting software for intraday and daily timeframe SARIMAX forecasting model. Capable of forecasting on any asset class with backtesting capability across various parameter sets customizable by the user.

Implementation of Time Series

A personal end-to-end machine learning project that seeks to predict stock prices from economical indicators for a variety of USA-based companies.

Stock Forecasting

Easy to follow stock price analysis forecasting techniques on Indian stock data

Stocks Forecasting for MAANG | MLOps using ZenML | Streamlit UI

image caption generator, dog breed classifier, stock forecasting 🤖🖼️ Порождение подписей на русском языке к изображениям (Python, Keras). Собрал нейросеть из двух частей – свёрточная и рекуррентная части. Получил датасет путём перевода на русский датасета Flickr 8k с помощью Yandex Translate API. Получил метрику BLEU равной 0.51.

Progetto di tesi: rete LSTM multivariata con sentiment analysis per la previsione dei titoli in borsa

PredictIt is a stock price forecasting web application based on LSTM algorithm chosen after an comprehensive comparative analysis with 5 other ML models.

Порождение подписей к изображениям. Классификация изображений. Прогнозирование временных рядов

A stock market forecaster using parallelized Monte Carlo simulations enhanced by machine learning (ML) techniques.

Analyzing and predicting Google's stock prices through detailed data exploration and advanced LSTM models. This project involves data preprocessing, creating time-series sequences, constructing and training LSTM networks, and evaluating their performance to forecast future stock prices utilizing Python and Machine Learning libraries.