Part 1)
List and briefly describe the nine-step process in con-ducting a neural network project.
Minimum 225 words
Part 2)
What are the common challenges with which sentiment analysis deals? What are the most popular application areas for sentiment analysis? Why?
Minimum 225 words
Part 3)
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) What is MLP, and how does it work? Explain the function of summation and activation weights in MLP-type ANN.
Minimum 140 words each question.
Part 4)
5) Explain the relationship among data mining, text min- ing, and sentiment analysis.
6) In your own words, define text mining, and discuss its most popular applications.
7) What does it mean to induce structure into text-based data? Discuss the alternative ways of inducing structure into them.
8) What is the role of NLP in text mining? Discuss the capa- bilities and limitations of NLP in the context of text mining.
Minimum 140 words each question.
Checklist
Total 225*2 + 140*4 + 140*4 = 1570 words (round to 1600).
Each part needs to be attached as separate file.
Plagairism report must for each part
APA formatting and each part needs to have at least 2 references.
