Introduction to Deep Learning
This training is the entry-point to Deep Learning. I will introduce you to the field and provide you with working knowledge that allows you to apply Deep Learning to your use-cases.
Two days of hands-on training containing:
- Learn the Deep Learning basics. What is the difference between Artificial Intelligence, Machine Learning, and Deep Learning? Are they all the same?
- Explore Python for Deep Learning. We will have a look at Jupyter notebooks, relevant modules, and how to go production ready with your Neural networks.
- Consider Deep Learning workstations. What kinds of hardware and software guarantee success?
- Investigate why it is time for Deep Learning. How to come to train your first Neural Network in about one hour of work?
- Apply Deep Learning for classifications and regressions. Learn how to classify data such as texts, and images. And learn how to extrapolate new data from experiences.
- Learn about the basic Neural Network Building Blocks. What are models, layers, losses, metrics, activation functions and optimizers?
- Establish a reusable template of a Neural Network training pipeline. Start with data of any sort and end with an evaluated Neural Network.
- Learn and apply Deep Learning best practices. Grow a good understanding about hyper-parameter tuning.