Gain a better understanding of deep learning techniques and TensorFlow software in this two-day course.
Deep learning with TensorFlow
Course outline
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Cost: $2000 per person
Location: UTS Faculty of Engineering and IT
Deep learning involves algorithms modelled on human brain functions that learn from large amounts of diverse data to solve complex problems. Its applications include facial recognition, virtual assistants, and more.
In this course you’ll explore popular Deep Learning algorithms in detail. You'll also learn TensorFlow, an open-source software for machine learning applications, and how it can be used to solve real-world problems.
Target audience
This course is intended for anyone interested in deep learning and using TensorFlow.
Course objectives
After completing this course you will be able to:
- Develop an understanding of deep learning fundamentals
- Understand how deep learning algorithms can be applied and the background of these algorithms
- Program in TensorFlow and apply TensorFlow to solve machine learning problems
- Able to apply some of the tools available for tackling common deep learning problems
- Identify any knowledge gaps and prepare for potential further studies in the field of deep learning
Day outline
- Program topics
- Introduction to TensorFlow
- Image classification
- Sentiment analysis: CNN, RNN
- Neural machine translation
- Generative adversarial networks
- Image generation
- Summary and conclusions
About the presenters
Richard Xu is an Associate Professor in machine learning and a leading researcher in the fields of machine learning, deep learning, data analytics and computer vision. He is the founder and director of the UTS DataLounge, which provides customised short courses for organisations seeking expertise in the field of machine learning. Richard is also a core member of the Innovation in IT Services and Applications research centre and the Global Big Data Technologies Centre at UTS.
