1. What is deep learning? What can deep learning do that traditional machine-learning methods cannot? 2. List and briefly explain different learning paradigms/ methods in AI. 3. What is representation learning, and how does it relate to machine learning and deep learning? 4. List and briefly describe the most commonly used ANN activation functions. 5. What is MLP, and how does it work? Explain the function of summation and activation weights in MLP-type ANN. 6. Cognitive computing has become a popular term to define and characterize the extent of the ability of machines/ computers to show “intelligent” behavior. Thanks to IBM Watson and its success on Jeopardy!, cognitive computing and cognitive analytics are now part of many realworld intelligent systems. In this exercise, identify at least three application cases where cognitive computing was used to solve complex real-world problems. Summarize your findings in a professionally organized report. .

1. 1. What is deep learning? What can deep learning do that
traditional machine-learning methods cannot?
2. List and briefly explain different learning paradigms/
methods in AI.
3. What is representation learning, and how does it relate to
machine learning and deep learning?
4. List and briefly describe the most commonly used ANN
activation functions.
5. What is MLP, and how does it work? Explain the function of
summation and activation weights in MLP-type ANN.
6. Cognitive computing has become a popular term to define
and characterize the extent of the ability of machines/
computers to show “intelligent” behavior. Thanks to IBM
Watson and its success on Jeopardy!, cognitive computing and
cognitive analytics are now part of many realworld intelligent
systems. In this exercise, identify at least three application
cases where cognitive computing was used to solve complex
real-world problems. Summarize your findings in a
professionally organized report.