Abstract
In recent years, there is a revolution in the applications of machine learning which is because of advancement and introduction of deep learning. With the increased layers of learning and a higher level of abstraction, deep learning models have an advantage over conventional machine learning models. There is one more reason for this advantage that there is a direct learning from the data for all aspects of the model. With the increasing size of data and higher demand to fi nd adequate insights from the data, conventional machine learning models see limitations due to the algorithm they work on. The growth in the size of data has triggered the growth of advance, faster and accurate learning algorithms. To remain ahead in the competition, every organization will defi nitely use such a model which makes the most accurate prediction. In this paper, we will present a review of popularly used deep learning techniques.
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CITATION STYLE
Kumar, V., & Garg, M. L. (2018). Deep learning techniques and their applications: A short review. Bioscience Biotechnology Research Communications, 11(4), 699–709. https://doi.org/10.21786/bbrc/11.4/22
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