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Assignment - Python Programming Questions
Q1. Briefly Explain the NLP application tasks performed and its significance.
Q2. Take Text of your choice - do the following analytics
a. No of words
b. No of sentences
c. No of Paragraphs
d. No of unique words
e. Which word appeared maximum no of times.
Q3. Take Text of your choice: 10 Sentences maximum. Do NER model.
Q4. Take 50 to 100 Reviews of Hotel, Online store - Do the Sentiment Analysis.
Q5. Briefly explain TF-IDF and its significance in NLP.
Q6. Explain list of NLP algorithms used for any 5 use cases of NLP.
Please submit with Notebook/ Data files used.
Python code to extract information about product details from data files and load them into a consistent SQL database
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Explain the differences between a variable and data types. What other source did you find that helped you improve your understanding of Python Programming.
You need to use python code allows the user to use a menu to select and then generate pick-3 or pick-4 lottery number generator.
Design a program to input three numbers from the user, find the largest of the three numbers, and display the three numbers along with the largest numbers.
Write a string expression whose value is the string equivalent of each these variables joined by a single period .
Write a program that reads the name of a data file which contains student ids (such as c1234500) and their scores. The program will find and print the average score, the number of students processed.
Write a script named copyfile.py. this script should prompt the user for the names of two text files. the contents of the first file.
Design a brute-force algorithm (write a Python program) for detecting fakecoin. Design a decrease by constant and conquer algorithm for detecting the fake coin.
QBUS 2310 Management Science Assignment. What is the optimal production policy and what is the profit under this policy
Create variables, store the information for the two payees in these variables, and then output the contents to the console.
Create a new DataFrame (2nd DataFrame) by removing all the rows with null/missing values in the 1st DataFrame and calculate the number of rows removed
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