Deep Learning
Machine Learning and Deep Learning
... machine learning. Machine learning has gained a lot of attention of researchers nowadays due to its distinct ...machine learning have been discussed in this ...machine learning is not as ...
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Deep Learning: A Vision for Computer
... Machine learning (ML) and deep learning ...this, deep learning is the branch of ML which outperformed the conventional techniques of machine ...and deep learning are ...
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Deep Learning as a Frontier of Machine Learning: A Review
... Deep learning, a family of machine learning algorithms, is inspired by the biological process of neural networks is dominating in many applications and proving its advantage over conventional machine ...
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List of Deep Learning Models
... Abstract. Deep learning (DL) algorithms have recently emerged from ma- chine learning and soft computing ...several deep learning (DL) algorithms have been recently introduced to ...
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Deep learning evaluation using deep linguistic processing
... We discuss problems with the standard ap- proaches to evaluation for tasks like visual question answering, and argue that artificial data can be used to address these as a com- plement to current practice. We demonstrate ...
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Deep Learning for Dialogue Systems
... on deep learning, deep belief networks (DBNs) with deep neural networks (DNNs) have been applied to domain and intent classification tasks (Sarikaya et ...filling, deep learning ...
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Machine Learning and Deep Learning Methods for Cybersecurity
... Manual detection of cybersecurity threats is not accurate as that of detection of cybersecurity threats by machine learning and deep learning. One of the simple and easy methods is to train the ...
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Detection of Glaucoma with Deep Learning
... Glaucoma is an ocular disorder caused due to increased uid pressure in the optic nerve. It damages the optic nerve subsequently and causes loss of vision. The available scanning methods are Heidelberg Retinal Tomography ...
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Deep Learning-An Upcoming Technology
... Unsupervised learning had a catalytic effect in reviving interest in deep learning, but has since been overshadowed by the successes of purely supervised ...unsupervised learning to become far ...
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The potential of deep learning in marketing : insights from predicting conversion with deep learning
... by deep learning. In recent years deep learning has been at the forefront of many breakthroughs in image recognition, speech recognition and natural language ...processing. Deep ...
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Review on: Deep Learning and Applications
... Network, Deep Learning and Decision Tree Learning are just piece of the ...profound learning research through barlications over the ongoing years in logical ...
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Deep Learning for Conversational AI
... From a research perspective, the design of spoken dialogue systems provides a number of significant challenges, as these systems depend on: a) solving several difficult NLP and decision-making tasks; and b) combining ...
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Advanced Machine Learning Approach: Deep Learning
... machine learning is undergoing its golden age as deep learning becomes gradually the pioneer in this ...field. Deep learning uses multiple layers to represent information abstractions ...
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Learning Abstract Classes using Deep Learning
... Since CNNs are very popular at the moment and perceived — in parts of the computer vision community — as obtain- ing human like performance we wanted to test their applica- bility on visual tasks slightly outside the ...
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Continual deep learning via progressive learning
... of deep learning requires a plethora of design decisions and ex- tensive tuning of hyperparameters to ensure good performance, ...various deep learning formulations and architectures applied ...
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Deep Learning for Dialogue Systems
... the Deep Learning Technology Center at Microsfot Re- ...on deep learning models for scaling natural user interfaces to multiple ...machine learning and its applications to ...
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Deep Learning: Approaches and Challenges
... popular deep learning tools and libraries that are available to construct and execute efficiently deep learning ...Environment, deep learning toolk- its provide a development ...
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Deep Learning with Go
... TensorFlow [3] is probably the most known deep learning framework. TensorFlow was originally developed by the Google Brain team. It is now an open source platform. TensorFlow has stable Python and C++ APIs. ...
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Acceleration of Deep Learning on FPGA
... In recent years, artificial intelligence and deep learning have shown their utility and ef- fectiveness in solving many real world computation intensive problems. At the center of this resurgence is the ...
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Deep Learning: A Review
... Abstract. Deep learning is an emerging area of machine learning (ML) ...The deep learn- ing methodology applies nonlinear transformations and model abstractions of high level in large ...in ...
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