Deep learning is a modern method that has been successfully applied in various domains. Deep learning has various applications such as image processing and text classification. Since the successful rate of deep learning is very high in other domains, so it is applied to agriculture methods too. Deep learning covers several layers of neural networks designed to perform more cultured tasks. Some of the deep learning models provide remarkable results, and in terms of scale they are not matched with humans. Each layer uses the outcome of previous result as input and whole network is trained as a single chain. Deep learning platform is a platform which helps users to build different deep learning architectures or facilitate users to apply deep learning to a wide range of business applications with apps and services. One of the main differences between machine learning and deep learning is deep learning requires more data for classification whereas small data are enough for classification in machine learning. The most popular deep learning tools are theno, kera, tensor-flow, py-torch and tool-box. Examples of deep learning are image processing and text classification. Figures 1.7 and 1.8 show working model of image and text classification.
Some of the deep learning architects are shown in Figure 1.9.
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