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Same pattern appears in different places: They can be compressed! What about training a lot of such “small” detectors and each detector must “move around”. 9 Nov 2016 brains seem to. Sources: https://www.macs.hw.ac.uk/~dwcorne/Teaching/introdl.ppt . computations. Blankevoort T., Neural Networks and Deep Learning, slides .. www.hpc.lsu.edu/training/tutorials.php#upcoming.Learning. algorithm. pixel 1. pixel 1. pixel 2. Andrew Ng. Machine learning and Learning. algorithm. Feature representation. Andrew Ng. Tutorial outline. Deep Learning Tutorial. ???. Hung-yi Lee. Deep learning attracts lots of attention. Google Trends. Deep learning obtains many exciting results. 2007. 2009. 1 from “Learning Deep Architectures for AI”; Yoshua Bengio; FTML Vol. 2, No. 1 (2009) error signal. Source: Hinton's 2009 tutorial on Deep Belief Networks. 8 Feature engineering is the process of using domain knowledge of the data to create features that make machine learning algorithms work. • “When working on a 30 Nov 2017 Deep learning algorithms attempt to learn (multiple levels of) . www.wildml.com/2015/09/recurrent-neural-networks-tutorial-part-1- Data and machine learning. Amount of data Andrew Ng. Computer vision. Learning algorithm. Feature representation . Tutorial: deeplearning.stanford.edu Deep Learning. aka or related to. Deep Neural Networks. Deep Structural Learning. Deep Belief Networks. etc,. DL is providing breakthrough results in speech Deep Reinforcement Learning; Two applications: Playing Atari & AlphaGo Deep learning (a.k.a. representation learning) seeks to learn rich hierarchical representations (i.e. features) .. Deep Learning Tutorial [Powerpoint slides]. Retrieved