The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.
Machine learning is a branch of artificial intelligence in which systems improve their performance on a task by learning patterns from data rather than following explicitly programmed rules. It is broadly divided into supervised learning for classification and regression from labeled examples, unsupervised learning for clustering and dimensionality reduction on unlabeled data, and reinforcement learning for learning optimal actions through trial-and-error interaction with an environment. Common algorithms include decision trees, support vector machines, ensemble methods such as random forests and gradient boosting, and neural networks, chosen based on data characteristics, interpretability needs, and computational constraints. Industry surveys suggest most organizations remain in experimentation or pilot phases with machine learning, with only about a third reporting they have begun scaling programs organization-wide. Machine learning underlies applications across nearly every domain, including predictive maintenance, credit scoring, medical diagnosis support, and recommendation systems. As an open-access machine learning journal (an ML journal), IJACSA publishes comparative studies and applied research spanning these algorithm families.
Published in International Journal of Advanced Computer Science and Applications (IJACSA) · list last refreshed September 2026
Critical systems are increasingly being integrated with machine learning (ML) models, which exposes them to a range of adversarial attacks.The vulnerability of machine learning systems to hostile attacks has drawn a lot…
In today’s rapidly evolving technological landscape, the ethical dimensions of information technology (IT) have become increasingly prominent, influencing everything from algorithmic decision-making to data privacy and c…
Artificial intelligence (AI) based chatbots leverage programmed software instructions to simulate human speech and user interaction. These versatile tools can be employed in various domains, from managing smart home devi…
Information is disseminated through images in newspapers, periodicals, the internet, and academic journals. With the aid of various tools such as Adobe, GIMP, and Corel Draw, distinguishing between an original image and…
With the continuous development and changes in the global financial markets, financial risk management has become increasingly important for the stable operation of enterprises. Traditional financial risk management meth…
Small-scale livestock farmers experience significant losses because of decreased productivity caused by decline in pasture production brought on by climate change. Technology in livestock farming introduced the idea of "…
Football is both a popular sport and a big business. Managers are concerned about the important decisions that team managers make when it comes to player transfers, player valuation issues, and particularly the determina…
In the context of the increasing prevalence of diabetes, this work focuses on integrating causal inference with Machine Learning (ML) for early diagnosis and effective management of diabetes. We applied a series of advan…
Understanding learning styles is essential for learners and instructors to identify strengths and weaknesses in the education system. Although the Felder-Silverman Learning Style Model (FSLSM) is commonly used for this p…
Utilisation of Educational Data Mining (EDM) can be useful in predicting academic performance of students to mitigate student attrition rate, allocation of resources, and aid in decision-making processes for higher educa…
