Tutorial on a number of topics in Deep Learning View on GitHub Author. Deep learning is an AI function and subset of machine learning, used for processing large amounts of complex data. Moreover, let us assume thatThe following figure depicts a recurrent neural network (with $5$ lags) learning and predicting the dynamics of a simple sine wave.Recurrent neural network predicting the dynamics of a simple sine wave.The following figure depicts a neural network fit to a synthetic dataset generated by random perturbations of a simple one dimensional function.Consider the following deep neural network with two hidden layers.The following figure depicts the training data and the samples generated by a conditional variational auto-encoder. Python 3.5; tensorflow 1.4; pytorch 0.2.0; The deeplearning algorithms includes (now): Logistic Regression logisticRegression.py; Multi-Layer Perceptron (MLP) mlp.py; Convolution Neural Network (CNN) cnn.py; Denoising Aotoencoder (DA) da.py Deep learning is primarily a study of multi-layered neural networks, spanning over a great range of model architectures. Deep Learning Tutorial by LISA lab, University of Montreal (Jan 6 2015). A deep learning-based tool to automatically replace censored artwork in hentai with plausible reconstructions. • I believe you have seen lots of exciting results before. In this course we study the theory of deep learning, namely of modern, multi-layered neural networks trained on big data. Image recognition, text processing and classification examples are provided here. Master Deep Learning, and Break into AI. View My GitHub Profile. Free Online Books. The tutorials presented here will introduce you to some of the most important deep learning algorithms and … Welcome to our deep-learning tutorials page. 深度学习-从入门到应用. Natural Language Inference with Deep Learning (NAACL 2019 Tutorial) This is a simple placeholder page that offers access to the slides for the 2019 NAACL tutorial on Natural Language Inference with Deep Learning by Sam Bowman and Xiaodan Zhu.. You can find the slides here (PDF, 10MB). This GIT repository accompanies the UKP lectures and seminars on Deep Learning for Natural Language Processing. Deep Learning for NLP - Tutorial. If you are just getting started with deep learning and Deeplearning4j, these tutorials will help clarify some of the concepts you will need to build neural networks. Contribute to Britefury/deep-learning-tutorial-pydata development by creating an account on GitHub. If you are just getting started with deep learning and Deeplearning4j, these tutorials will help clarify some of the concepts you will need to build neural networks. Deep Learning Tutorial 李宏毅 Hung-yi Lee. This screencast shows how to build a Linear Classifier using Deeplearning4j.This tutorial is a series of videos and code examples that show a complete data pipeline.By applying a more complex algorithm, Lenet, to MNIST, you can achieve 99 percent accuracy.