In this video is about de-mystifying Deep Learning for developers many of whom could benefit from understanding and using Deep Learning in their day-to-day job.
Deep Learning has taken the world of Computer Science by storm yet for many of us it remains an elusive sci-fi-like buzzword. After years of feature engineering in Computer Vision and Natural Language Processing, we have finally come to the point where, we can feed raw data to a Neural Network, similar to how our brains work, and expect results that can surprise us in their high accuracy.
This talk is about de-mystifying Deep Learning for developers many of whom could benefit from understanding and using Deep Learning in their day-to-day job. It covers the background and brief theoretical grounds in the first half but shows actual working code and examples in the rest. We will overview convolutional Neural Networks and then cover network design techniques such as pooling, dropout and local connections.
The examples of this talk are in Keras on top of TensorFlow and aimed to build real-world models in the field of Text Processing. We will detect language of a code file by training on examples.
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