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The book provides an overview of the analyzing and predicting stock price movements using statistical and data science tools using R open source software with hypothetical stock data sets. It provides a short introduction to R software to enable the user to understand analysis part in the later part.
The book will not go into details of suggesting when to purchase a stock or what at price. The tools presented in the book can be used as a guiding tool in decision making while buying or selling the stock.
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Showing 2 featured editions. View all 2 editions?
Edition | Availability |
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1
Stock price analysis through Statistical and Data Science tools: An Overview
2021, Vinaitheerthan Renganathan
Paperback
in English
9354579736 9789354579738
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Libraries near you:
WorldCat
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2
Stock Price Analysis Through Statistical and Data Science Tools: An Overview
2021, Draft2Digital
in English
1393996345 9781393996347
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Libraries near you:
WorldCat
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Book Details
Table of Contents
Chapter 1: Introduction
Chapter 2: R Software
Chapter 3: Graphical Analysis
Chapter 4: Stock price prediction using Statistical tools
Chapter 8: Stock price prediction using Support Vector Machine (SVM)
Chapter 5: Stock price prediction using Artificial Neural Network (ANN)
Chapter 6: Stock price prediction using Decision Tree
Chapter 7: Stock price prediction using Random Forest
Chapter 8: Stock price prediction using Naïve Bayes method
Chapter 9: Stock price prediction using Deep Learning
Chapter 10: Stock price prediction using Recurrent Neural Network (RNN)
Chapter 11: Stock price prediction using Long Short Term Memory (LSTM)
Chapter 12: Stock price prediction using Text Mining models and Sentiment analysis
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Feedback?October 16, 2021 | Edited by statbooks | Table of content, image, |
October 16, 2021 | Created by statbooks | Added new book. |