International Journal of Machine Learning (IJML) is a peer-reviewed international journal dedicated to publishing high-quality research in machine learning and artificial intelligence. The journal welcomes original research articles, review papers, and applied studies that demonstrate novelty, methodological rigor, and practical relevance.

IJML covers a broad range of topics, including supervised and unsupervised learning, deep learning, reinforcement learning, natural language processing, computer vision, explainable AI, trustworthy AI, and interdisciplinary real-world applications. The journal is committed to maintaining high editorial standards, ethical publication practices, and transparent peer-review processes to support global scholarly communication.