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

… 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 …

… 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. …

… in developing deep learning … learning approaches; (2) reviewing deep SNNs composed of
feedforward, fully connected spiking neural layers; (3) spiking convolutional neural 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 …

… 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 …

… neural networks and deep learning methods. We describe the inspiration for artificial neural
networks and how the methods of deep learning … of artificial neural networks that play an …

… Deep Learning is a new machine learning field that gained a lot of interest over the past few
… learning tool for many of the complex problems. In this paper we used Deep Neural Network …