Financial factors analysis for acquisition premium and anticipation using extreme gradient boosting and deep recurrent neural network

Financial factors analysis for acquisition premium and anticipation using extreme gradient boosting and deep recurrent neural network

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2019.

Xehetasun bibliografikoak
Egile Nagusiak:	Rayhan, Mohammad, Sultana, Samiha, Majid, Annur
Beste egile batzuk:	Alam, Md. Golam Rabiul
Formatua:	Thesis
Hizkuntza:	en_US
Argitaratua:	Brac University 2020
Gaiak:	Financial factors Deep learning XGBoost Machine learning
Sarrera elektronikoa:	http://hdl.handle.net/10361/14060

Antzeko izenburuak

Yield prediction for precision agriculture using extreme gradient boosting and support vector regression
nork: Ahmed, Md. Sabbir, et al.
Argitaratua: (2021)

Aﬀective state recognition through analysis of electroencephalogram signals by using extreme gradient boosting
nork: khan, Md. Sakib, et al.
Argitaratua: (2021)

A comparative study of deep learning methods for automating road condition characterization
nork: Ruhi, Zurana Mehrin, et al.
Argitaratua: (2021)

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

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

Prediction on large scale data using extreme gradient boosting
nork: Sawon, Md.Tariq Hasan, et al.
Argitaratua: (2016)

Investigation assistant with suspect anticipating intelligence
nork: Abdullah, Saqueeb, et al.
Argitaratua: (2019)

Corn leaf disease detection using deep convolution neural network
nork: Rabbi, Rawhatur, et al.
Argitaratua: (2023)

Analysis of real-time hostile activitiy detection from spatiotemporal features using time distributed deep convolutional neural networks, recurrent neural networks and attention-based mechanisms
nork: Siddique, Labib Ahmed, et al.
Argitaratua: (2022)

Flight fare prediction using machine learning
nork: Noyon, Md. Shaim Hosan, et al.
Argitaratua: (2024)

Prostate cancer detection using deep learning neural network with transfer learning approach
nork: Badhon, Ariful Islam Mahmud, et al.
Argitaratua: (2022)

A macroeconomic model for forecasting crude oil prices with Feedforward Neural Network Grid Search Experimentation
nork: Aunjum, Md. Ragib, et al.
Argitaratua: (2021)

Skin cancer detection and classification using multiple optimized deep convolutional neural network
nork: Sakir, Adnan, et al.
Argitaratua: (2023)

An active-learning based training-schedule for biomedical image segmentation on deep neural networks
nork: Hassan, Mehadi, et al.
Argitaratua: (2021)

Learning a deep neural network for predicting phishing website
nork: Das, Robat, et al.
Argitaratua: (2019)

Analysing Facebook user risk using machine learning algorithm
nork: Barua, Arnab, et al.
Argitaratua: (2021)

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

Detecting Deepfake images using deep convolutional neural network
nork: Dhar, Arpita, et al.
Argitaratua: (2022)

Machine learning based analysis and prediction of crop yield and prices of Aman, Aus and Boro rice
nork: Bhattacharjee, Ruposri, et al.
Argitaratua: (2024)

Bangali Handwritten characters classification using Deep Convolutional Neural Network
nork: Sikder, Shihab Uddin, et al.
Argitaratua: (2022)

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

KDANet: optical recognition for Bangla language using deep neural networks
nork: Rabbi, Kazi Kamruzzaman, et al.
Argitaratua: (2023)

An efficient deep learning approach to detect skin Cancer
nork: Islam, Ashfaqul, et al.
Argitaratua: (2022)

Self-learning game bot using deep reinforcement learning
nork: Ananto, Azizul Haque
Argitaratua: (2018)

Cassava leaf disease classification using deep learning and convolutional neural network ensemble
nork: Shahriar, Hasan, et al.
Argitaratua: (2022)

Implementation of machine learning to estimate the air pollutants such as Carbon dioxide, methane, nitrous oxide and total greenhouse gas emissions in Bangladesh
nork: Biswas, Sunanda, et al.
Argitaratua: (2022)

Predicting crime using deep learning
nork: Shihab, Muhammad Nafees, et al.
Argitaratua: (2024)

A modern technique to detect potholes by Computer Vision and Deep Learning
nork: Saif, Muntasir Mahmud, et al.
Argitaratua: (2023)

Damaged road detection using Image Processing and Deep Learning
nork: Swadesh, Shimran Mahbub, et al.
Argitaratua: (2022)

Deep learning /
nork: Goodfellow, Ian
Argitaratua: (2016)

Micro-learning modules are linked to enhanced retention of the learners and can be geared toward subconscious knowledge acquisition in an organization
nork: Siddique, Noman
Argitaratua: (2024)

ROBB: recurrent proximal policy optimization reinforcement learning for optimal block formation in bitcoin blockchain network
nork: Dutta, Amit
Argitaratua: (2024)

DeepWPD: A deep learning based wavelet packet decomposition to remove Moiré pattern from screen capture images.
nork: Khan, Ibrahim
Argitaratua: (2023)

Performance analysis of machine learning classi ers for detecting PE malware
nork: Azmee, ABM.Adnan, et al.
Argitaratua: (2020)

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

An implementation and analysis of deep learning models for the detection of wheat diseases
nork: Zubair, Ahmad, et al.
Argitaratua: (2024)

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

Classiﬁcation of damaged vegetation areas using convolutional neural network over satellite images
nork: Haque, Samiha, et al.
Argitaratua: (2021)

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

Prediction of bipolar disorder from mental episodes using machine learning approach
nork: Tasmeem, Sumaiya, et al.
Argitaratua: (2023)