… deep supervised learning (also recapitulating the history of backpropagation), unsupervised
learning, reinforcement learning & … for short programs encoding deep and large networks. …

… Many of the deep learning techniques utilizes the neural network architectures, to classify a
… referred as the deep neural networks. In deep neural networks the word deep points to the …

… We’ll learn the core principles behind neural networks and deep learning by attacking a
concrete problem: the problem of teaching a computer to recognize handwritten digits. This …

… This review summarizes machine learning and deep learning … learning (ML). ML contains
many models and methods, including deep learning (DL) and artificial neural networks (ANN). …

… experimentation with more sophisticated and deep neural architectures than was previously
… of the potential of deep learning. This book discusses neural networks from this modern …

… Finally, we consider how deep neural network models might help us understand brain …
Deep learning by backpropagation Say we want to train a deep neural network model with …

… methods, such as support vector machine, random forest, and artificial neural network. …
A deeply stacked artificial neural network is utilized in deep learning. With the deep learning …

… This literature review provides an insight of deep learning neural networks. Based on the
applications and the design methods, deep networks are analysed and categorized into …

… It is a pleasure to acknowledge the assistance in my deep learning neural network and related
… basic concepts in neural networks and which are used in deep learning neural networks. …

… of (deep) neural networks and explain algorithmic advances to learn network parameters …
Here, we introduce a deep neural network that constructs a deep architecture by taking auto-…