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Benefits of Applying Deep Learning with Neural Networks
Deep learning has the capability to execute tasks using multiple neural networks which allows faster processing and channeling of a plethora of data processes into a combined platform. In the near future, more and more AI tasks.
Deep learning is applied to tasks wherein, massive data needs to be implemented. The neural networks in deep learning learn through multiple layers and bring out accurate results. Hence, for tasks like a calibrated performance of the AV, neural networks are important. For instance, in autonomous vehicles (AV), deep learning combined with ANNs or artificial neural networks provides the capacities of perception, planning and controlling to the vehicle.
Especially when high accuracy is required, deep learning performs in expected capability, in comparison with what machine learning can deliver. A high detection rate and low false-positive rate makes deep learning a preferred methodology for arriving at accurate calculations. Since the amount of data processing in deep learning is extensive, the hardware for processing includes GPU, TPU, FPGA for training and deployment of the model. It is applicable across computer vision, natural language processing or NLP, speech recognition, and gaming applications.
The capability to process multi-channel data through multi-layered learning has heightened the need for deep learning for multifaceted applications within the industry. Deep neural networks have delivered high success rates in computation-
Roger Brown- Company of Cogito Tech LLC | AI | ML.