Deep Learning

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Deep Learning: Definition, Resources, Comparison with Machine Learning

Deep learning is sometimes referred to as the intersection between machine learning and artificial intelligence. It is about designing algorithms that can make robots intelligent, such a face recognition techniques used in drones to detect and target terrorists, or pattern recognition / computer vision algorithms to automatically pilot a plane, a train, a boat or a car. Many deep learning algorithms (clustering, pattern recognition, automated bidding, recommendation engine, and so on) -- even though they appear in new contexts such as IoT or machine to machine communication -- still rely on relatively old-fashioned techniques such as logistic regression, SVM, decision trees, K-NN, naive Bayes, Bayesian modeling, ensembles, random forests, signal processing, filtering, graph theory, gaming theory, and many others.

Source: Data Science Central. http://www.datasciencecentral.com/profiles/blogs/deep-learning-definition-resources-comparison-with-machine-learni

Thanks for sharing, Vincent Granville

Resources for beginners

   10 Deep Learning Terms Explained in Simple English 
   Deep Learning Demystified 
   An Introduction to Deep Learning and it’s role for IoT/ future cities 
   Deep Learning vs Machine Learning vs Pattern Recognition 
   Step-by-step video courses for Deep Learning and Machine Learning 
   Deep learning simplified (video) 

More advanced resources

   Implementing a Distributed Deep Learning Network over Spark 
   Is deep learning a Markov chain in disguise? 
   Deep learning & XgBoost : Winning it hands down ! 
   Deep Learning with Professor Geoff Hinton 
   Decision Boundaries for Deep Learning and other Machine Learning cl... 
   Free deep learning book - MIT press