International Journal of Data Science and Analytics
Data Science has been established as an important emergent scientific field and paradigm driving research evolution in such disciplines as statistics, computing science and intelligence science, and practical transformation in such domains as science, engineering, the public sector, business, social science, and lifestyle. The field encompasses the larger areas of artificial intelligence, data analytics, machine learning, pattern recognition, natural language understanding, and big data manipulation. It also tackles related new scientific challenges, ranging from data capture, creation, storage, retrieval, sharing, analysis, optimization, and visualization, to integrative analysis across heterogeneous and interdependent complex resources for better decision-making, collaboration, and, ultimately, value creation. The International Journal of Data Science and Analytics (JDSA) brings together thought leaders, researchers, industry practitioners, and potential users of data science and analytics, to develop the field, discuss new trends and opportunities, exchange ideas and practices, and promote transdisciplinary and cross-domain collaborations.
Shan Suthaharan (March 2019)
Regression-based supervised learning of autosteering of a road car featuring a delayed steering response
- Journal Title
- International Journal of Data Science and Analytics
- Volume 1 / 2016 - Volume 7 / 2019
- Print ISSN
- Online ISSN
- Springer International Publishing
- Additional Links
- Industry Sectors
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