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Machine Learning Techniques and Applications
(An International Journal)
OPEN ACCESS
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Editor In-Chief

Dr. Sanjeev Sharma
RGPV, Bhopal, M.P., India
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About Journal
IJMLTA is high quality peer-reviewed journal, where every article will be peer-reviewed by several experts in the field. Upon acceptance, articles will be published in the latest open volume.
The journal aims to be a global forum of, for, and by the community and offers:
- Rapid peer review under the expert guidance of a global Editorial Board.
- No color or page charges, free submission, and is free to access for the first one year of publication
- High visibility
- Opportunities to Societies / Conferences / Institutes / Laboratories /Corporate to ‘partner’ with the Journal and enjoy the benefit of planning and publishing issues in hot areas of research, without being under the pressure of publishing a full-fledge journal.
IJMLTA welcomes research and review papers related to Machine Learning Techniques and applications, but not limited to the areas of:
- Linear Regression
- Logistic Regression
- Decision Tree
- Support Vector Machine
- Naive Bayes
- K-Nearest Neighbour
- Random Forest
- Dimentionality Reduction Algorithms
- Gradient Boosting Algorithms
For a complete list of topics, please visit: Aims & Scopes
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