Data analysis on the Bangladesh share market using Machine-Learning

Data analysis on the Bangladesh share market using Machine-Learning

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.

Bibliografiske detaljer
Main Authors:	Sadman, Syed Hassan, Rahat, Hasib Al, Hamim, Atikur Rahman, Al Kafi, Sultan Gias Uddin, Khan, Nasik Ali
Andre forfattere:	Rahman, Tanvir
Format:	Thesis
Sprog:	English
Udgivet:	Brac University 2021
Fag:	Data Mining Machine Learning Stock Market Prediction Linear Regression Analysis K-Nearest Neighbour Support Vector Machine Lasso Analysis Market share > Bangladesh
Online adgang:	http://hdl.handle.net/10361/14991

Lignende værker

Intrusion of Malware (DDoS) detection in IoT devices using Machine Learning on Cyberspace
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A machine learning approach to detect depression and anxiety using supervised learning
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Flood prediction using machine learning models
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Udgivet: (2022)

Effectiveness of data mining in predicting heart diseases
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Udgivet: (2018)

Performance analysis of machine learning algorithms for Malware classification
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Udgivet: (2023)

Cardiovascular disease prediction model using Machine Learning Algorithm
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Travel time prediction using machine learning and weather impact on traffic conditions
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Supervising vehicle using pattern recognition
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An introduction to support vector machines : and other kernel-based learning methods /
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Predicting stock market trend from twitter feed and building a framework for Bangladesh
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Udgivet: (2018)

Weather forecasting using Deep Learning
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EMG controlled bionic robotic arm using artificial intelligence and machine learning
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A deep learning approach to predict crypto-currency price by evaluating sentiment and stock market correlations
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Human recognition using wireless router signal
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Stock price prediction
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Application of CNN based architectures in detection of distracted drivers
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Finding ideal geographical location for businesses using machine learning technique
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Share market forecasting with LSTM neural network and sentimental trend prediction
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Pattern recognition with Quantum Support Vector Machine(QSVM) on near term quantum processors.
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A feature selection approach to determine obesity using machine learning method
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Forecasting Dhaka stock exchange prices using machine learning models: a Performance analysis
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Stock market prediction using ensemble learning
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Modelling and forecasting energy demand of Bangladesh using AI based algorithms
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Polycystic ovary syndrome detection using neural network.
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Machine learning based analysis and prediction of crop yield and prices of Aman, Aus and Boro rice
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A thesis on utilizing machine learning models to predict material hardship
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The applications of data mining and machine learning in Bangladesh for disease pattern analysis and prediction
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Enhancing crops production based on environmental status using machine learning techniques
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A new approach to select adaptive Intrinsic Mode Functions (IMFs) of Empirical Mode Decomposition (EMD)
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Detection of epileptic seizure using Support Vector Machine Classifier - extracted features from EEG signals
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Cyberbullying detection using sentiment analysis in social media
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