Here is the list of online workshops. Each one of them will be 4 hours long. Workshops will take place on 16th of April 2021.
AI FOR MANAGERS
Many data science or machine learning projects fail due to mistakes done during the project development. We can group the mistakes into a few most popular that if known earlier can make your project successful. The training also gives a better understanding of the topic of artificial intelligence for technical and non-technical managers. We go through the process of the AI transformation and show a few tips on how to make the transformation easy. Many managers also try to build machine learning related projects in an agile process in a similar way as it’s done in a typical software development project. We show how to do it right and structure the team. Another important topic that is covered in the training is related to quality and signs when to stop the development or research. Finally, we go through several business cases and show customers challenges, expectations and how we solved it
In the days where we have autonomous cars, drones, and automated medical diagnostics, we want to learn more about how to interpret the decisions made by the machine learning models. Having such information we are able to debug the models and retrain it in the most efficient way.
This training is dedicated to managers, developers and data scientists that want to learn how to interpret the decisions made by machine learning models. We explain the difference between white and black box models, the taxonomy of explainable models and approaches to XAI. Knowing XAI methods is especially useful in any regulated company. We go through the basic methods like the regression methods, decision trees, ensemble methods, and end with more complex methods based on neural networks.In each example, we use a different data set for each example. Finally, we show how to use model agnostic methods to interpret it and the complexity of the interpretability of many neural networks.
MACHINE LEARNING SECURITY
Neural networks are currently the most popular machine learning methods. One type of use cases are based on pattern recognition on images. Neural networks as any other solution is liable to security issues. In this training we go through potential leaks and vulnerabilities of neural networks. This training is dedicated to managers and data scientists that want to learn more on how to find leaks and secure a neural network.
In the first part of the training, we start with some examples of simple adversarial attacks and show how to generate simple images with noise that change the prediction of a network. The second part is on attack taxonomy. We explain different types of attacks and weaknesses of networks. This includes targeted and untargeted attacks. We show how to find out the vulnerability using white and black-box methods. The third section is on environment and how to inverse the gradient descent methods. We go deep into the math details of a gradient descent attack. Finally, we show the details of defense methods.
Each section ends with a simple exercise, we have four small exercises written in Python. The examples are developed in Tensorflow and Keras.