NECBF Deep Learning Traditional Machine Learning Methods & AI Discussion

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znyq

Computer Science

New England College of Business and Finance

Description

Task 1


Complete the following assignment in one MS word document:

Chapter 6– discussion question #1-5 & exercise 4


When submitting work, be sure to include an APA cover page and include at least two APA formatted references (and APA in-text citations) to support the work this week.
All work must be original (not copied from any source).

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

Excercise4

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 Chapter 6 • Deep Learning and Cognitive Computing 385 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


Need elobrated answers


Task 2

Go online and search for information about companies that have been harmed or bankrupted by a disaster. Choose one such company and create a brief case study about it. Successful narratives will focus on the manner in which the organization was impacted, including financial losses, losses of sales, or the need for layoffs. Your assignment should be 3-4 paragraphs in length.


No plagrism please


User generated content is uploaded by users for the purposes of learning and should be used following Studypool's honor code & terms of service.

Explanation & Answer

Attached.

Running head: DEEP LEARNING

1

Deep Learning
Name of Student
Institution Affiliation

DEEP LEARNING

2
Deep Learning

What is deep learning?
Deep learning is a category of machine learning inspired by artificial neural networks
responsible for networks that are designed to learn from unstructured data.
What can deep learning do that the traditional machine-learning method cannot?
Deep learning is well suited for data of large size while machine learning is suited for
small data sets. Deep learning performs well in solving complex problems such as speech
recognition and natural language processing.
List and briefly explain different learning paradigms/ methods in AI.
There are three basic learning paradigms in AI namely supervised learning,
reinforcement learning, and unsupervised learning. In supervised learning, one has to give
both input and the output expected for the computer to learn. It is the most basic type of
learning as it is based on commonly known algorithms. An example of supervised learning is
Linear regression (Sotiropoulos & Tsihrintzis, 2016).
Unsupervised learning is characterized by having only the input and the computer is
expected to generate a pattern in the data based on the input only. The computer learns from
finding structures in the data. Reinforcement learning on the other hand is characterized by
computers determining the ideal behavior within a given context to optimize performance.
This learning paradigm teaches a computer how to respond to certain inputs o...


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