THE USE OF AUTOMATED MACHINE LEARNING METHODS AND TOOLS IN DATA SCIENCE




Abstract:
Data Science needs powerful and efficient, yet comprehensive and easy methods and tools to use. Machine learning methods are especially important for generating useful knowledge and insights from rapidly growing amounts of data. However, their use is not always straightforward. Full or partial automation of a machine learning process has been a long-time goal which has become increasingly important during the last couple of years. In this work, fully automated machine learning tools for typical data science tasks are discussed. An empirical comparison of actual automated machine tools and common manual methods is provided for different programming environments based on Java, R and Python languages.

CITATION:

IEEE format

V. Miškovic, S. Adamović, “The Use of Automated Machine Learning Methods and Tools in Data Science,” in Sinteza 2017 - International Scientific Conference on Information Technology and Data Related Research, Belgrade, Singidunum University, Serbia, 2017, pp. -. doi:  

APA format

Miškovic, V., Adamović, S. (2017). The Use of Automated Machine Learning Methods and Tools in Data Science. Paper presented at Sinteza 2017 - International Scientific Conference on Information Technology and Data Related Research. doi:

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