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Use the Health_care.csv file. This file consists of a labeled dataset of 10,000 users on Twitter.

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Need help to complete below assignment in 10 hours

Question #1: Use the Health_care.csv file. This file consists of a labeled dataset of 10,000 users on Twitter.

Descriptions are captured from profile of users and labeled are assigned to them based on the profession (1= healthcare professional, 0= Non-healthcare professional) Use a representative image to form a wordcloud using the healthcare professional users' descriptions

Create the document term frequency matrix (X) using CountVectorizer Use multinomial NB to form a predictive model and test the accuracy of your model Use 70% of data for tarining and consider 30% of data for testing.

(Use random_state=0) hc_related is your dependent variable Use Random Forest to form a predictive model and test the accuracy of your model Use 70% of data for tarining and consider 30% of data for testing. (Use random_state=0) hc_related is your dependent variable Use Stochastic Gradient Descent to form a predictive model and test the accuracy of your model Use 70% of data for tarining and consider 30% of data for testing.

(Use random_state=0) hc_related is your dependent variable Use logistic regression to form a predictive model and test the accuracy of your model Use 10-fold cross validation to test the performace of your model hc_related is your dependent variable Use LDA to find 5 topics in description of health professional users Use the 5 detected topics in the last step and apply the logistic regression to develope a predictive model.

Check the performance the model using the accuracy metric. Use 70% of data for tarining and consider 30% of data for testing. (Use random_state=0) hc_related is your dependent variable Use word-embedding method to develope a prredictive model. Use logistic regression in your work. Use 70% of data for tarining and consider 30% of data for testing. (Use random_state=0) hc_related is your dependent variable # Write your answer here (part1) # Write your answer here (part2) # Write your answer here (part3) # Write your answer here (part4) # Write your answer here (part5) # Write your answer here (part6) # Write your answer here (part7) # Write your answer here (part8) # Write your answer here (part9)

Question #2: Use the game_of_thrones.csv file. The file contains network data for character relationships within George R. R. Martin's A Storm of Swords, the third novel in his series A Song of Ice and Fire (also known as the HBO television adaptation Game of Thrones). This data was originally compiled by A. Beveridge and J. Shan, "Network of Thrones," Math Horizons Magazine , Vol. 23, No. 4 (2016), pp. 18-22. What is the degree distribution?(plot it) What is the average network clustering value? Which character has the highest betweenness centrality? Which character has the highest eigenvector centrality? Which character has the highest pagerank value? Apply community detection using louvain algorithm (resolution=1).

What is the number of communities? # Write your answer here (part1) #

Write your answer here (part2) # Write your answer here (part3) # Write your answer here (part4) # Write your answer here (part5) # Write your answer here (part6) Output: You need to provide answers in the designated cell for each question (don't delete the existing comments in the cells). You need to make sure that your final file contains both codes and results (don't clear the outputs). Save your file in the .ipynb format (as it is right now). Create a zip-folder and put your file in it. Upload the zip-folder into Canvas (Assignment #4) All the assignments should be submitted by Sunday Dec 4 at 11:59 PM. No late submission will be accepted I will not accept any submission by email or any other method, so make sure that you submit the file in a right place at the right time.

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