Authors :
Aravind Gangavarapu; P V S Pranay; Polisetti Likhit Sai
Volume/Issue :
Volume 9 - 2024, Issue 9 - September
Google Scholar :
https://tinyurl.com/395mstad
Scribd :
https://tinyurl.com/a5sa3xjk
DOI :
https://doi.org/10.38124/ijisrt/IJISRT24SEP330
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
This document explains how artificial
intelligence (AI) and the stock market can work
together. Among the more important ones are stock
pattern detection and stock prediction using AI. The goal
of stock market prediction is to forecast the future value
of a company's fiscal stocks. The application of machine
literacy, which bases predictions on the values of current
stock request indicators by training on their historical
values, is a recent development in stock request
vaticination technology.
Several models are used by machine learning itself
to facilitate and authenticate vaccination. The study
focuses on prognosticating stock values using LSTM
based machine literacy. Considered factors are volume,
low, high, open, and closed.
Transfer literacy was the model we used for the
stock.
Keywords :
Long-Short Term Memory(LSTM), Convolutional Neural Networks, Transfer Learning(VGG- 16).
References :
- Stanford University CS231n Convolutional Neural Networks for Visual Recognition.
- Yun-Cheng Tsai, Jun-Hao Chen, Jun-Jie Wang (2018) Predict Forex Trend via Convolutional Neural Networks.
- Stephanie Thurrott—November 22 ,2021 “The Best Ways to Commu- nicate with Someone Who Doesn’t Hear Well”
- M.S. Magnusson (1999), Discovering hidden time patterns in behavior: T-patterns and their detection.
- A. Razavian et al (2014) CNN Features off-the-shelf: an Astounding Baseline for Recognition
- C. Olah (2015) Understanding LSTM Networks.
This document explains how artificial
intelligence (AI) and the stock market can work
together. Among the more important ones are stock
pattern detection and stock prediction using AI. The goal
of stock market prediction is to forecast the future value
of a company's fiscal stocks. The application of machine
literacy, which bases predictions on the values of current
stock request indicators by training on their historical
values, is a recent development in stock request
vaticination technology.
Several models are used by machine learning itself
to facilitate and authenticate vaccination. The study
focuses on prognosticating stock values using LSTM
based machine literacy. Considered factors are volume,
low, high, open, and closed.
Transfer literacy was the model we used for the
stock.
Keywords :
Long-Short Term Memory(LSTM), Convolutional Neural Networks, Transfer Learning(VGG- 16).