Deep Learning and Cognitive Computing

Answer below questions and exercise

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.

To answer above there is no page restriction, but you have to provide in-text citation and references to the each question that is answered.

Exercise 4: This must be answered in one full page of content along with in-text citation and peer reviewed reference

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 real world

APA Format Only

In-text citations mandatory

Only 6 peer reviewed references (No typical websites or something ends with .com can be considered as peer reviewed)

References should be in APA format and must be in the alphabetical order

No plagiarism/Spinbot/Synonymic words please

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.