Deep Learning is an advancement in machine learning technology that uses neural networks for building prediction models. In this course, students use TensorFlow, an open-source and industry standard library for machine learning developed by Google Brain.
TensorFlow allows distribution of computation across CPUs and multiple GPUs on a single computer—an enhancement that enables development of high-performance prediction models.
Students will build prediction models of different complexities, from simple linear logistic regression to convolutional neural network (CNN) and recurrent neural network (RNN) with long Short-term memory (LSTM).
By the end of the class, students have a working deep learning environment and sample projects. The class prepares students to pursue a career in data sciences.
Topics Include:
- Deep learning and TensorFlow
- Multilayer perceptrons
- Advanced multilayer perceptrons
- Convolutional neural networks
- Recurrent neural networks
- RNN - prediction with multilayer perceptron
- RNN - prediction with long short term memory networks
Skills Needed: Moderate level of computer programming ability in Python and basic understanding of machine learning models.