Why NLP processes human language in ML Python - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to print a simple greeting using NLP.

ML Python

text = "Hello, world!"
print([1])

Drag options to blanks, or click blank then click option'

Aprint(text)

BText

Ctext

Dhello

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'Text' instead of 'text' causes a NameError.

Putting print(text) inside print() prints the greeting followed by 'None'.

The variable 'text' holds the string to print. Using 'text' prints the greeting.

2fill in blank

medium

Complete the code to split a sentence into words using NLP.

ML Python

sentence = "I love learning NLP"
words = sentence.[1](' ')
print(words)

Drag options to blanks, or click blank then click option'

Afind

Bjoin

Creplace

Dsplit

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'join' causes a TypeError because it expects an iterable.

Using 'replace' causes a TypeError because it requires two arguments.

The split(' ') method breaks the sentence into a list of words separated by spaces.

3fill in blank

hard

Fix the error in the code to count word frequency.

ML Python

from collections import Counter
text = "NLP helps computers understand language"
words = text.split()
word_counts = Counter([1])
print(word_counts)

Drag options to blanks, or click blank then click option'

Awords

Btext

CCounter

Dsplit

Attempts:

3 left

💡 Hint

Common Mistakes

Passing 'text' counts characters, not words.

Passing 'Counter' or 'split' counts characters, not words.

The Counter needs a list of words, so we pass 'words', not the original text string.

4fill in blank

hard

Fill both blanks to create a dictionary of word lengths for words longer than 3 letters.

ML Python

words = ['chat', 'ai', 'language', 'data']
lengths = {word: [1] for word in words if len(word) [2] 3}
print(lengths)

Drag options to blanks, or click blank then click option'

Alen(word)

B<

C>

Dword

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' filters shorter words, not longer.

Using 'word' instead of len(word) gives wrong values.

We use len(word) to get length and '>' to filter words longer than 3 letters.

5fill in blank

hard

Fill all three blanks to create a dictionary of uppercase words and their lengths for words shorter than 6 letters.

ML Python

words = ['hello', 'world', 'python', 'ai']
result = { [1]: [2] for w in words if len(w) [3] 6 }
print(result)

Drag options to blanks, or click blank then click option'

Aw.upper()

Blen(w)

C<

Dw

Attempts:

3 left

💡 Hint

Common Mistakes

Using '>' filters longer words, not shorter.

Using 'w' as key does not convert to uppercase.

We use w.upper() as key, len(w) as value, and filter words with length less than 6.

Practice

1. Why do we use Natural Language Processing (NLP) in computers?

easy

A. To store large amounts of data

B. To make computers run faster

C. To help computers understand and work with human language

D. To improve computer hardware

Solution

1. Step 1: Understand the purpose of NLP

   NLP is designed to let computers understand human language, like English or Spanish.

2. Step 2: Compare options to NLP's goal

   Only To help computers understand and work with human language matches this goal. Other options relate to speed, storage, or hardware, which NLP does not focus on.

3. Final Answer:

   To help computers understand and work with human language -> Option C

4. Quick Check:

   NLP purpose = understanding language [OK]

Hint: NLP = computers + human language understanding [OK]

Common Mistakes:

• Confusing NLP with hardware improvements
• Thinking NLP speeds up computers
• Mixing NLP with data storage tasks

2. Which of the following is the correct way to split a sentence into words in Python for NLP?

easy

A. sentence.add()

B. sentence.join()

C. sentence.remove()

D. sentence.split()

Solution

1. Step 1: Recall Python string methods for splitting text

   The method split() breaks a string into a list of words by spaces.

2. Step 2: Check other options for correctness

   join() combines words, add() and remove() are not string methods.

3. Final Answer:

   sentence.split() -> Option D

4. Quick Check:

   Split text = split() method [OK]

Hint: Split text into words with split() [OK]

Common Mistakes:

• Using join() instead of split()
• Trying to add or remove on strings
• Confusing string methods with list methods

3. What will be the output of this Python code snippet used in NLP?

text = "I love AI"
words = text.split()
print(len(words))

medium

A. 3

B. 1

C. 4

D. Error

Solution

1. Step 1: Split the text into words

   The string "I love AI" split by spaces gives the list ["I", "love", "AI"].

2. Step 2: Count the number of words

   The list has 3 elements, so len(words) returns 3.

3. Final Answer:

   3 -> Option A

4. Quick Check:

   Words count = 3 [OK]

Hint: Count words by splitting and using len() [OK]

Common Mistakes:

• Counting characters instead of words
• Expecting 4 because of spaces
• Thinking split() returns a string

4. Find the error in this NLP code snippet:

sentence = "Hello world"
words = sentence.split
print(words)

medium

A. Wrong variable name for sentence

B. Missing parentheses after split method

C. print() cannot print lists

D. split() should be replaced with join()

Solution

1. Step 1: Check method usage

   The method split needs parentheses to be called: split().

2. Step 2: Verify other options

   Variable name is correct, print() can print lists, and join() is not for splitting.

3. Final Answer:

   Missing parentheses after split method -> Option B

4. Quick Check:

   Method call needs () [OK]

Hint: Remember to add () when calling methods [OK]

Common Mistakes:

• Forgetting parentheses on method calls
• Confusing split() with join()
• Thinking print can't show lists

5. You want to build a simple NLP system to detect if a sentence expresses happiness or sadness. Which step is most important to start with?

hard

A. Break the sentence into words and check for happy or sad words

B. Train a computer to run faster

C. Store the sentence in a database without changes

D. Change the sentence to uppercase only

Solution

1. Step 1: Understand the goal of sentiment detection

   Detecting happiness or sadness means analyzing the meaning of words in the sentence.

2. Step 2: Identify the first NLP step

   Breaking the sentence into words allows checking for keywords that show emotion.

3. Final Answer:

   Break the sentence into words and check for happy or sad words -> Option A

4. Quick Check:

   Sentiment detection starts with word analysis [OK]

Hint: Start by splitting text to find emotion words [OK]

Common Mistakes:

• Focusing on speed instead of meaning
• Ignoring word-level analysis
• Changing case without purpose