Deep Learning Workshop
YOW! Data 2018 - 16 May
Venture into deep learning with this 2-day workshop that will take you from the mathematical and theoretical foundations to building models and neural networks in TensorFlow. You will apply as you learn, working on exercises throughout the workshop. To enhance learning, a second day is dedicated to applying your new skills in team project work.
This hands-on workshop is ideal for both data science and programming professionals, who are interested in learning the basics of deep learning and embarking on their first project.
Noon van der Silk
Noon has 18+ years experience in various forms of software engineering, application development, and the design and implementation of machine learning + AI systems. Within AI he has a special interest in the field of computer vision and interactive art.
Noon has a research background, obtaining a Masters in Pure Mathematics, with a focus on quantum computing.
Noon is particularly passionate about empowering people through skill development, which he does through the training courses over at the Braneshop.
- Target Audience
- Anyone with Python programming experience who is interested in applying deep learning!
- 2 days
- An intuitive understanding of the components of machine learning systems
- Experience building neural networks in TensorFlow and TFLearn
- Clear understanding of convolutions and representation learning
- Clear understanding of embeddings in deep learning, and how to learn them
- Practical real-world model development in TensorFlow
FUNDAMENTALS, CONVOLUTIONS, EMBEDDINGS, EXERCISES
The first day will see us learn as a group, working through exercises and building up a solid base of knowledge around deep learning.
We will cover key concepts in the field and introduce them with examples
The second day will see us consolidate our knowledge by working in small groups on complete projects. A few project options will be provided across image processing, natural language processing (NLP), and generative models.
This day will build real-world experience in deep learning model development.
- Laptop with wifi-internet access.
- An internet connection