Start up business solution using machine learning

Start up business solution using machine learning

This thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018.

Bibliografiske detaljer
Main Authors:	Sohan, Saad Ahmed, Nakib, Ayman, Ahmed, Tanvir
Andre forfattere:	Alam, Md. Ashraful
Sprog:	English
Udgivet:	BRAC University 2018
Fag:	Data science Artificial intelligence Machine learning Business solution
Online adgang:	http://hdl.handle.net/10361/10102

Lignende værker

Alumni opportunities using machine learning
af: Siaum, Arshif Sharlimin, et al.
Udgivet: (2019)

Bank loan prediction using machine learning
af: Mahottam, Parthosarothi, et al.
Udgivet: (2023)

Machine learning approach for improving decision support in ICU
af: Siddiquee, Mohib Billah, et al.
Udgivet: (2019)

Performance comparison of transformer-based models for multi-reasoning in machine reading comprehension
af: Sayma, Sadika, et al.
Udgivet: (2024)

Predicting climate induced floods using machine learning
af: Saleh, Chowdhury Nafis, et al.
Udgivet: (2022)

Real time performance analysis on DDoS attack detection using machine learning
af: Suvra, Debashis Kar, et al.
Udgivet: (2021)

Impact of machine learning and deep learning on biomedical applications and healthcare industry
af: Kabir, Md Saif, et al.
Udgivet: (2024)

Multimodal human detection in disaster situations using deep learning & artificial intelligence
af: Rafat, Md. Tasbi, et al.
Udgivet: (2023)

Handwritten Bangla character recognition to braille pattern conversion using image processing and machine learning
af: Abir, Tawhidur Rahman, et al.
Udgivet: (2019)

A machine learning approach to credit default prediction and Individual credit scoring
af: Rahman, Md. Jaber, et al.
Udgivet: (2018)

Exploring the intersection of machine learning and explainable artificial intelligence: An analysis and validation of ML models through XAI for intrusion detection
af: Rahman, Masroor, et al.
Udgivet: (2023)

Detecting propagandistic poster title: a machine learning approach
af: Mahmood, Riaz, et al.
Udgivet: (2024)

Implementing A.I based solutions to understand & predict consumer sentiment
af: Bin Ahmed, Omar
Udgivet: (2023)

Application of machine learning in credit risk assessment: a prelude to smart banking
af: Dhruba, Mir Ishrak Maheer, et al.
Udgivet: (2019)

A deep learning approach for prediction of ADHD using brain structure
af: Siam, Shafin Ahad, et al.
Udgivet: (2024)

Rumor detection in Bangla using machine learning & deep learning
af: Ahmed, Md Istiaq, et al.
Udgivet: (2023)

Heart attack prediction using machine learning and XAI
af: Ahsan, Mumtahina
Udgivet: (2023)

Forecasting Dhaka stock exchange prices using machine learning models: a Performance analysis
af: Alam, Md. Iftekharul, et al.
Udgivet: (2024)

Comparison of machine learning techniques to predict cardiovascular disease
af: Jaber, Mir Mohammad, et al.
Udgivet: (2019)

Machine learning approach for ECG analysis and predicting different heart diseases
af: Tithi, Sushmita Roy, et al.
Udgivet: (2019)

Classifying insect pests from image data using deep learning
af: Mohsin, Md. Raiyan Bin, et al.
Udgivet: (2022)

Crop prediction based on geographical and climatic data using machine learning and deep learning
af: Alif, Al Amin, et al.
Udgivet: (2019)

Predicting obesity: a comparative analysis of machine learning models incorporating different features
af: Rahman, Md.Sakibur, et al.
Udgivet: (2023)

Predicting peak performance of a cricket player using machine learning and data analytics
af: Azam, Akif, et al.
Udgivet: (2023)

Use of predictive analytics in Business
af: Raihana, Fabiha
Udgivet: (2023)

Flood prediction using machine learning models
af: Syeed, Miah Mohammad Asif, et al.
Udgivet: (2022)

Machine learning-based approach on predicting online shopping addiction using EEG signals
af: Nawer, Nafisa, et al.
Udgivet: (2023)

Flood prediction using ensemble machine learning models
af: Rahman, Tanvir
Udgivet: (2024)

A machine learning approach to detect depression and anxiety using supervised learning
af: Ullas, Md Tahmidur Rahman, et al.
Udgivet: (2019)

Yoga posture recognition using the deep learning process
af: Islam, Abidul, et al.
Udgivet: (2023)

A machine learning-based approach for data analysis to ascertain suicidal individuals from Social media users
af: Nahar, Fatiha Binte Kamrun, et al.
Udgivet: (2023)

Intelligent parking system using machine learning
af: Abrar, Md. Ishtiak, et al.
Udgivet: (2023)

NLP-based AI robot for intelligent interaction
af: Dastagir, Golam, et al.
Udgivet: (2024)

Machine learning with PySpark : With natural language processing and recommender systems /
af: Singh, Pramod
Udgivet: (2022)

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

Detection and classification of Mango Leaf diseases utilizing convolutional neural network models
af: Ferdous, Md.Rubaiat, et al.
Udgivet: (2024)

Cardiovascular disease prediction model using Machine Learning Algorithm
af: Arefin Mirdha, MD Shamsul
Udgivet: (2023)

Machine learning with quantum computers /
af: Schuld, Maria
Udgivet: (2021)

Predicting depression in Bangladeshi undergraduates using machine learning
af: Choudhury, Ahnaf Atef, et al.
Udgivet: (2019)

Making AI intelligible :
af: Cappelen, Herman