DeepLearning.TV's video: Use Cases - Ep 12 Deep Learning SIMPLIFIED

Despite its popularity, machine vision is not the only Deep Learning application. Deep nets have started to take over text processing as well, beating every traditional method in terms of accuracy. They also are used extensively for cancer detection and medical imaging. When a data set has highly complex patterns, deep nets tend to be the optimal choice of model. Demo URLs Clarifai - http://www.clarifai.com Metamind - https://www.metamind.io/language/twitter As we have previously discussed, Deep Learning is used in many areas of machine vision. Facebook uses deep nets to detect faces from different angles, and the startup Clarifai uses these nets for object recognition. Other applications include scene parsing and vehicular vision for driverless cars. Deep Learning TV on Facebook: https://www.facebook.com/DeepLearningTV/ Twitter: https://twitter.com/deeplearningtv Deep Nets are also starting to beat out other models in certain Natural Language Processing tasks like sentiment analysis, which can be seen with new tools like MetaMind. Recurrent nets can be used effectively in document classification and character-level text processing. Deep Nets are even being used in the medical space. A Stanford team was able to use deep nets to identify 6,642 factors that help doctors better predict the chances of cancer survival. Researchers from IDSIA in Switzerland used a deep net to identify invasive breast cancer cells. In drug discovery, Merck hosted a deep learning challenge to predict the biological activity of molecules based on chemical structure. In finance, deep nets are trained to make predictions based on market data streams, portfolio allocations, and risk profiles. In digital advertising, these nets are used to optimize the use of screen space, and to cluster users in order to offer personal ads. They are even used to detect fraud in real time, and to segment customers for upselling/cross-selling in a sales environment. What is your favorite deep learning application? Please comment and share your thoughts. Credits Nickey Pickorita (YouTube art) - https://www.upwork.com/freelancers/~0147b8991909b20fca Isabel Descutner (Voice) - https://www.youtube.com/user/IsabelDescutner Dan Partynski (Copy Editing) - https://www.linkedin.com/in/danielpartynski Marek Scibior (Prezi creator, Illustrator) - http://brawuroweprezentacje.pl/ Jagannath Rajagopal (Creator, Producer and Director) - https://ca.linkedin.com/in/jagannathrajagopal