Data Science & Mathematics Journal | IJCSE Volume 3 Issue 2 – Physics, Chemistry & Machine Learning Research
Data Science & Mathematics Journal – IJCSE Volume 3 Issue 2
The International Journal of Computer Science Engineering Techniques (IJCSE) (ISSN: 2455-135X) brings together peer-reviewed research in data science, mathematics, physics, chemistry, and machine learning. Publish in a leading open access journal for computational, physical, and mathematical sciences. Fast peer review, global exposure, and dedicated author support.
    Featured Research – Data Science, Math, Physics & Chemistry
Download recent peer-reviewed articles in mathematics, physics, chemistry, and machine learning, free and open access.
Survey of Geofencing Algorithms
Authors: Pratik Deshmukh, Anuja Bhajibhakre, Shubham Gambhire, Aman Channe, Dr. Neeta Deshpande
Download Data Science ArticleAn Efficient Heart Disease Prediction using Various Data Mining Techniques
Authors: A Krishna, Ch Narsimha Chary, M Rakesh Chowdary, Dr R P Singh
Download Machine Learning ResearchMeasuring Non-Functional Requirement via Cloud Hosted Application in Favour of Booking System
Authors: Anamika Sharma
Download Applied Math ArticleInteroperability Between Distributed Anomaly Detection Systems: A Federated Learning Approach Using Java
Authors: Hitesh Ninama
Download Physics Data Science ArticleOptimizing Patient Data Management in Healthcare Information Systems Using IoT and Cloud Technologies
Authors: Koteswararao Dondapati, Purandhar. N
Download Chemistry IoT ArticleWhy Publish in a Data Science, Mathematics or Physics Journal?
- Peer-reviewed, open access research in data science, mathematics, machine learning, and physics
 - International authority in journal of chemistry and interdisciplinary science
 - Prominent platform for new findings in theoretical/applied mathematics and analytics
 - Accelerated and transparent manuscript review
 - Dedicated support from an expert editorial board for physicists, chemists, and mathematicians
 
Your Author Resources & Journal Tools
Peer Reviewed – Advance Data Science & Mathematics
All data science, math, and physics articles in IJCSE are double peer-reviewed; your results are fast-tracked, indexed, and open for rapid citation and discovery.
