Deep Learning

| January 9, 2019 | 0 Comments

Deep Learning is a hierarchical learning methodology based on artificial neural networks which are algorithms inspired by the structure and function of the brain. It has applications in wide-range of industries these days such as face-recognisers working at massive scales, robotics, speech translation, text analysis, improving customer experience, autonomous vehicles etc.

In this course we will take a “hands-on approach” and start will implementation of basic building blocks such as training a simple perceptron and move to design and train a deep convolution neural network. Course will concentrate in developing both mathematical knowledge and implementation capabilities. The implementations will be python based using TensorFlow and Keras. After establishing our foundation in convolutional neural networks we will start looking into applications of deep learning in both spatial as well as time-series data and explore various network architectures suited for each. The objective is to help you build a career in AI and Machine learning, to make you comfortable enough that you can understand various learning problems and develop your own deep learning based solutions.

Course Outline: PDF

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Category: Teaching

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