Abstract
Nowadays, machine learning plays a vital role in software industry and is of utmost demand in day-to-day life activities. Machine learning has emerged as one of the popular technology for solving real-world applications as autonomous vehicle, speech recognition, image processing, natural language processing and so on. As per Intel/IDC, about 76% of Indian companies are feeling the dearth of skilled talented professional in machine learning. By 2025, it is estimated that the machine learning sector in software industries will grow up to the $16 billion share. In this paper, different machine learning model based on supervised approach is proposed and compared the performance in terms of accuracy on training data and test data, precision, recall and F measure. Python is used for experimental work.
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Malviya, A. (2020). Machine Learning: An Overview of Classification Techniques. In: Giri, V., Verma, N., Patel, R., Singh, V. (eds) Computing Algorithms with Applications in Engineering. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-15-2369-4_33
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DOI: https://doi.org/10.1007/978-981-15-2369-4_33
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