{"repo":"JordiCorbilla/stock-prediction-deep-neural-learning","free":true,"listed":false,"github":"https://github.com/JordiCorbilla/stock-prediction-deep-neural-learning","clone":"git clone https://github.com/JordiCorbilla/stock-prediction-deep-neural-learning.git","description":"Predicting stock prices using a TensorFlow LSTM (long short-term memory) neural network for times series forecasting","language":"Jupyter Notebook","stars":689,"topics":["machine-learning","deep-learning","deep-neural-networks","yfinance","lstm-neural-networks","lstm-model","recurrent-neural-networks","stock-prediction","stock-prices","market-data"],"license":"CC0-1.0","category":"machine-learning","readme_excerpt":"Stock prediction using deep neural learning Predicting stock prices can be a challenging task as it often does not follow any specific pattern. However, deep neural learning can be used to identify patterns through machine learning. One of the most effective techniques for series forecasting is using LSTM (long short-term memory) networks, which are a type of recurrent neural network (RNN) capable of remembering information over a long period of time. This makes them extremely useful for predicting stock prices. This TensorFlow implementation of an LSTM neural network can be used for time series forecasting. Successful prediction of a stock's future price can yield significant profits for investors . Quickstart (Conda) This project uses Python 3.12 and TensorFlow 2.18.1. If you prefer pip inside an existing env: Jupyter users should select the stock-prediction kernel. If it does not appear: 1) Introduction Predicting stock prices is a complex task, as it is influenced by various factors such as market trends, political events, and economic indicators. The fluctuations in the stock prices are driven by the forces of supply and demand, which can be unpredictable at times. To identify patterns and trends in stock prices, deep learning techniques can be used for machine learning. Long short-term memory (LSTM) is a type of recurrent neural network (RNN) that is specifically designed for sequence modeling and prediction. LSTM is capable of retaining information over an extended per","default_branch":null,"files":null,"tree":[],"storefront":"/r/JordiCorbilla","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/JordiCorbilla/stock-prediction-deep-neural-learning/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}