[HTML][HTML] Machine learning algorithms for depression: diagnosis, insights, and research directions

S Aleem, N Huda, R Amin, S Khalid, SS Alshamrani… - Electronics, 2022 - mdpi.com
Over the years, stress, anxiety, and modern-day fast-paced lifestyles have had immense
psychological effects on people's minds worldwide. The global technological development …

A new benchmark on machine learning methodologies for hydrological processes modelling: a comprehensive review for limitations and future research directions

ZM Yaseen - Knowledge-Based Engineering …, 2023 - … journals.publicknowledgeproject.org
The best practice of watershed management is through the understanding of the
hydrological processes. As a matter of fact, hydrological processes are highly associated …

A comparative analysis of machine learning algorithms to predict alzheimer's disease

M Bari Antor, AHMS Jamil, M Mamtaz… - Journal of …, 2021 - Wiley Online Library
Alzheimer's disease has been one of the major concerns recently. Around 45 million people
are suffering from this disease. Alzheimer's is a degenerative brain disease with an …

Comparative study of regressor and classifier with decision tree using modern tools

JS Kushwah, A Kumar, S Patel, R Soni… - Materials Today …, 2022 - Elsevier
Abstract Machine Learning is one of the importantareas for modeling the data and itcan be
saidthat this is the core part of the field of Data Science. Supervised Machine Learning …

An efficient way of identifying alzheimer's disease using deep learning techniques

K Gupta, N Jiwani, P Whig - Proceedings of Third Doctoral Symposium on …, 2022 - Springer
Alzheimer's disease has recently emerged as a big worry. This condition affects around 45
million people. Alzheimer's disease is a deteriorating brain illness through an unknown …

Machine learning and marketing: A systematic literature review

V Duarte, S Zuniga-Jara, S Contreras - IEEE Access, 2022 - ieeexplore.ieee.org
Even though machine learning (ML) applications are not novel, they have gained popularity
partly due to the advance in computing processing. This study explores the adoption of ML …

[HTML][HTML] A combined method for preparation of landslide susceptibility map in Izmir (Türkiye)

C Kincal, H Kayhan - Applied Sciences, 2022 - mdpi.com
Landslide susceptibility maps (LSMs) have been used frequently by researchers for many
years in prediction of the occurrence of landslides. Since many landslides have occurred …

Sentiment analysis for distance education course materials: A machine learning approach

UÖ Osmanoğlu, ON Atak, K Çağlar… - Journal of Educational …, 2020 - dergipark.org.tr
Nowadays many companies and institutions are interested in learning what do people think
and want. Many studies are conducted to answer these questions. That's why, emotions of …

Machine Learning and Marketing: A Literature Review.

V Duarte, S Zuniga-Jara, S Contreras - Available at SSRN …, 2022 - papers.ssrn.com
Abstract Despite that Machine Learning (ML) applications is not novel, it has gained
popularity partly to the advance in computing processing and cost. Nevertheless, this it is not …

[HTML][HTML] Revolutionizing Education: Advanced Machine Learning Techniques for Precision Recommendation of Top-Quality Instructional Materials

X Xu - International Journal of Computational Intelligence …, 2023 - Springer
The integration of educational technology in the modern classroom has transformed the way
students learn yet challenges in providing high-quality materials persist. To address this, we …