Classification of arsenic contamination in water using Machine learning

Classification of arsenic contamination in water using Machine learning

Cataloged from PDF version of thesis report.

Bibliografiske detaljer
Main Authors:	Leon, Yeasir Hossain, Mosharrof, Adib
Andre forfattere:	Rahman, Mohammad Zahidur
Format:	Thesis
Sprog:	English
Udgivet:	BRAC University 2014
Fag:	Computer science and engineering
Online adgang:	http://hdl.handle.net/10361/2940

Lignende værker

Arsenic contamination : Bangladesh perspective /
Udgivet: (2003)

Arsenic contamination of groundwater in Bangladesh /
Udgivet: (2001)

Arsenic contamination of groundwater in Bangladesh /
Udgivet: (2001)

Arsenic contamination of groundwater in Bangladesh /
Udgivet: (2001)

Arsenic contamination of groundwater in Bangladesh /
Udgivet: (2001)

Text classification using machine learning algorithms
af: Hasnat, Fahim, et al.
Udgivet: (2018)

Status of arsenic test and exposure to arsenic-contaminated tubewell water: a population-based study in Southern Bangladesh
af: Dey, Nepal C, et al.
Udgivet: (2019)

A study on development of an arsenic test kit and some arsenic contamination issues /
af: Khair, Abul
Udgivet: (2003)

Lung cancer detection and classification using machine learning
af: Arefin, Mahbubul, et al.
Udgivet: (2023)

Using sentiment analysis & machine learning for security price forecasting
af: Roy, Jyotirmoy, et al.
Udgivet: (2016)

Bangla text classification using machine learning and deep learning techniques
af: Salehin, Kamrus, et al.
Udgivet: (2021)

Geogenic arsenic and Microbial contamination in drinking water sources: Exposure risks to the coastal population in Bangladesh
af: Saha, Ratnajit, et al.
Udgivet: (2022)

Heart disease prediction using techniques of classification in machine learning
af: Afrose, Sadia, et al.
Udgivet: (2021)

Machine learning engineering /
af: Burkov, Andriy
Udgivet: (2020)

Interpretable Bangla fake news classification using BERT and traditional machine learning approaches
af: Anan, Ramisa, et al.
Udgivet: (2023)

Diabetic retinopathy detection and classification by using deep learning
af: Hossain, Shahriar, et al.
Udgivet: (2022)

Learning computer programming using e-learning as a tool
af: Alam, Asharf, et al.
Udgivet: (2010)

Daily arsenic contamination associated with Gestational diabetes mellitus and neonatal outcome
af: Sinthi, Nudrat Ansari
Udgivet: (2016)

Comparative study of toxic comments classification using machine learning algorithms
af: Razzak, Razia, et al.
Udgivet: (2021)

Gene classification and pattern analysis using data mining and machine learning techniques
af: Ramisa, Aiman Jabeen, et al.
Udgivet: (2021)

Sound classification using deep learning for hard of hearing and deaf people
af: Habib, Md.Adnan, et al.
Udgivet: (2022)

Using machine learning on a diverse class of problems : from rainfall to criminal actions
af: Munira, Sirajum, et al.
Udgivet: (2016)

Performance analysis of machine learning algorithms for Malware classification
af: Bushra, Raisa Hasan, et al.
Udgivet: (2023)

Analysis and manipulation of the data set obtained from the study of pre-primary education development using machine learning
af: Khan, Sushmita Laila, et al.
Udgivet: (2014)

The use of alternative safe water option to mitigate the arsenic problem in Bangladesh : community perspective /
af: Jakariya, Md
Udgivet: (2003)

The use of alternative safe water option to mitigate the arsenic problem in Bangladesh : community perspective /
af: Jakariya, Md
Udgivet: (2003)

Pattern classification /
af: Duda, Richard O.
Udgivet: (2001)

A study of malware classification using deep learning
af: Rahman, Mohammad Muhibur, et al.
Udgivet: (2024)

Classification and Explanation of Different Internet of Things (IoT) Network Attacks using Machine Learning, Deep Learning and XAI
af: Tasnim, Anika, et al.
Udgivet: (2022)

A Review of groundwater arsenic contamination in Bangladesh: the millennium development goal era and beyond
af: Md. Yunus, Fakir, et al.
Udgivet: (2016)

Depression classification with MDD (Major Depressive Disorder) using signal processing and machine learning
af: Saleque, Shahriar, et al.
Udgivet: (2021)

Foundations of machine learning /
af: Mohri, Mehryar, et al.
Udgivet: (2018)

Classification of retinal diseases from OCT images using deep learning models
af: Mokarrom, Md Saif, et al.
Udgivet: (2024)

Remote monitoring and detection of water contamination in effluent treatment plants
af: Hossain, Akib, et al.
Udgivet: (2024)

Automation requirements engineering using machine learning
af: Abid, Md.Mehedy Hasan, et al.
Udgivet: (2022)

Cancer classification using deep learning from medical image data
af: Monir, Raiyan Janik, et al.
Udgivet: (2022)

Classification of peripheral blood cell images using deep learning
af: Aadi, Oyshik Ahmed, et al.
Udgivet: (2024)

Arsenic in tubewell water and health consequences: mitigation component
af: Jakariya, Md.
Udgivet: (2019)

Awareness and choice of options of Arsenic-free drinking water
af: Hadi, Abdullahel
Udgivet: (2019)

Bang-lish sentiment classification using deep learning
af: Saleheen, Abrar, et al.
Udgivet: (2023)