Deep learning has emerged in the last few years as a premier technology for building intelligent systems that learn from data.

Although using TensorFlow directly can be challenging, the modern tf.keras API beings the simplicity and ease of use of Keras to the TensorFlow project. Deep Learning ist eine Machine-Learning-Technik, mit der Computer eine Fähigkeit erwerben, die Menschen von Natur aus haben: aus Beispielen zu lernen. (eg. A Tutorial on Deep Learning Part 2: Autoencoders, Convolutional Neural Networks and Recurrent Neural Networks Quoc V. Le qvl@google.com Google Brain, Google Inc. 1600 Amphitheatre Pkwy, Mountain View, CA 94043 October 20, 2015 1 Introduction In the previous tutorial, I discussed the use of deep networks to classify nonlinear data. (eg. Deep Learning with Keras Tutorial in PDF - You can download the PDF of this wonderful tutorial by paying a nominal price of $9.99.

Predictive modeling with deep learning is a skill that modern developers need to know. Overview • Practical Recipes of Unsupervised Learning • Learning representations • Learning to generate samples • Learning to map between two domains • Open Research Problems 2. Deep neural networks, originally roughly inspired by how the human brain learns, are trained with large amounts of data to TensorFlow is the premier open-source deep learning framework developed and maintained by Google. PDF Documentation; Deep Learning Toolbox™ provides a framework for designing and implementing deep neural networks with algorithms, pretrained models, and apps. Tutorial on Deep Learning and Applications Honglak Lee University of Michigan Co-organizers: Yoshua Bengio, Geoff Hinton, Yann LeCun, Andrew Ng, and MarcAurelio Ranzato * Includes slide material sourced from the co-organizers . Deep Learning ist eine wichtige Technologie in fahrerlosen Autos, die es diesen ermöglicht, ein Stoppschild zu erkennen oder einen Fußgänger von einer Straßenlaterne zu unterscheiden. You can use convolutional neural networks (ConvNets, CNNs) and long short-term memory (LSTM) networks to perform classification and regression on image, time-series, and text data.

Complete Deep Learning book; Stanford UFLDL Tutorial “Deep Learning in Neural Networks: An Overview”, a survey paper on Deep Learning Participate in Deep Learning community. Google Group, DL Subreddit) Follow recent researches / researchers. Unsupervised Deep Learning Tutorial - Part 2 Alex Graves Marc’Aurelio Ranzato NeurIPS, 3 December 2018 gravesa@google.com ranzato@fb.com.

Introduction to Deep Reinforcement Learning Shenglin Zhao Department of Computer Science & Engineering The Chinese University of Hong Kong “RE.WORK DL Summit”) Timeline : Suggested – Infinity!

Noteworthy Resources.