Identification of fake news using machine learning in distributed system

Identification of fake news using machine learning in distributed system

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

Xehetasun bibliografikoak
Egile Nagusiak:	Saif, Mehruz, Kanon, MD. Kamal Haque, Hasan, Nazmul, Hossen, MD. Shamim, Anannya, Fatema Zohra
Beste egile batzuk:	Akhond, Mostafijur Rahman
Formatua:	Thesis
Hizkuntza:	English
Argitaratua:	Brac University 2021
Gaiak:	PySpark ML RDD(Resilient Distributed Dataset) Random Forest Factorization Machine Classifier Linear SVC Logistic Regression Machine Learning
Sarrera elektronikoa:	http://hdl.handle.net/10361/15199

Antzeko izenburuak

Detecting fake news on Covid-19 using machine learning algorithms
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Argitaratua: (2023)

FakeDetect: Bangla fake news detection model based on different machine learning classifiers
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Flood prediction using machine learning models
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SCAMM: detection and prevention of SQL injection attacks using a machine learning approach
nork: Alam, Auninda, et al.
Argitaratua: (2021)

Detecting online recruitment fraud by using machine learning
nork: Ghosh, Gitanjali, et al.
Argitaratua: (2021)

Emotion analysis using machine learning model and deep learning model on DEAP dataset
nork: Hasan, Anita, et al.
Argitaratua: (2022)

Chronic kidney disease detection using ensemble classi ers and feature set reduction
nork: Shawan, Naveed Rahman, et al.
Argitaratua: (2019)

The applications of data mining and machine learning in Bangladesh for disease pattern analysis and prediction
nork: Mahmud, Mahmudul Hasan
Argitaratua: (2021)

Performance analysis of intrusion detection systems using the PyCaret machine learning library on the UNSW-NB15 dataset
nork: Abdullah, et al.
Argitaratua: (2021)

Parking data analysis
nork: Ahamed, Kasfi, et al.
Argitaratua: (2023)

A machine learning based approach for DDos attack detection
nork: Tahrim, Tasmiah, et al.
Argitaratua: (2024)

Sentimental analysis of food review contents to improve food culture and the quality of virtual content using natural language processing and machine learning
nork: Sarkar, Ripa, et al.
Argitaratua: (2024)

A comparative performance analysis of accident anticipation with deep learning extractors
nork: Mostak, Alfi Mashab, et al.
Argitaratua: (2023)

A machine learning approach to detect DeepFake videos
nork: Hassan, Md. Mahedi, et al.
Argitaratua: (2021)

Effectiveness of data mining in predicting heart diseases
nork: Afrin, Shahria, et al.
Argitaratua: (2018)

Detection of fake identities on twitter using supervised machine learning
nork: Rahman, MD. Takiur, et al.
Argitaratua: (2019)

Unleashing potential: a data-driven exploration of identifying player potentialities through advanced analytics in sports
nork: Bhowmik, Prashanta, et al.
Argitaratua: (2024)

Machine learning In breast cancer prognosis and prediction
nork: Chowdhury, Shah Abul Hasnat, et al.
Argitaratua: (2023)

COVID-19 related fake news detection model
nork: Shondhy, Sumaiya Islam, et al.
Argitaratua: (2021)

Statistical analysis of network data flows and predictions using statistical and machine learning regression models
nork: Boateng, Albert, et al.
Argitaratua: (2024)

RetinalNet-500: a newly developed CNN model for eye disease detection
nork: Toki, Sadikul Alim, et al.
Argitaratua: (2023)

Mobile sensors based human activity recognition using machine learning with explainable ML
nork: Rahman, Raihan, et al.
Argitaratua: (2021)

Heart disease prediction system
nork: Amit, Tayab Al Azad, et al.
Argitaratua: (2022)

Fake profile detection in social media using image processing and machine learning
nork: Sen, Shuva, et al.
Argitaratua: (2021)

Botnet detection In IoT devices using machine learning
nork: Rouf, Shakir, et al.
Argitaratua: (2020)

ML based career suggestive system for informal job sector considering cognitive skills
nork: Tonny, Ms. Ayesha Siddika, et al.
Argitaratua: (2023)

Explainable artificial intelligence and model calibration for water quality prediction
nork: Hellen, Nakayiza
Argitaratua: (2022)

Detection of early stages of Parkinson's disease by analyzing fMRI data and machine learning approaches
nork: Neehal, Ahmed Hasin, et al.
Argitaratua: (2020)

Tiny-ML based person identification in dynamic motion
nork: Ahmed, Mirza Raiyan, et al.
Argitaratua: (2024)

A counseling system to predict the study path for freshmen
nork: Usha, Rowshni Tasneem, et al.
Argitaratua: (2019)

A machine learning approach to predict young voter enthusiasm based on non-political factors
nork: Rahman, Md. Nowroz Junaed, et al.
Argitaratua: (2021)

Multimodal approach to human detection in unconstrained environments using YOLOV7 for conventional, infrared & thermal cameras
nork: Rukaiya, Maymuna, et al.
Argitaratua: (2023)

An effective machine learning approach for sentiment analysis of restaurant reviews
nork: Karim, Rabita
Argitaratua: (2018)

A machine learning approach to analyze and predict rainfall in different regions of Bangladesh
nork: Rahee, Arnob, et al.
Argitaratua: (2021)

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

Document template identification and data extraction using machine learning and deep learning approach
nork: Roy, Kaushik, et al.
Argitaratua: (2024)

Credit card fraud detection using machine learning techniques
nork: Kabir, Tasmia, et al.
Argitaratua: (2021)

Multimodal fake news detection using text and image
nork: Biswas, Trisha, et al.
Argitaratua: (2024)

Multisystemic resilience :

Forecasting stock market prices using advanced tools of machine learning
nork: Anwar, Md. Tawhid, et al.
Argitaratua: (2019)