UMAP for dimensionality reduction in ML Python - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the UMAP class from the umap-learn library.

ML Python

from umap import [1]

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AKMeans

BPCA

CTSNE

DUMAP

Attempts:

3 left

💡 Hint

Common Mistakes

Importing PCA or TSNE instead of UMAP.

Trying to import from sklearn instead of umap.

The UMAP class is imported from the umap module to perform dimensionality reduction.

2fill in blank

medium

Complete the code to create a UMAP object with 2 output dimensions.

ML Python

reducer = UMAP(n_components=[1])

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A2

B1

C10

D3

Attempts:

3 left

💡 Hint

Common Mistakes

Using 3 or more components when 2 is needed for 2D plots.

Using 1 component which reduces to 1D, not 2D.

Setting n_components=2 reduces data to 2 dimensions for easy visualization.

3fill in blank

hard

Fix the error in the code to fit and transform data using UMAP.

ML Python

embedding = reducer.[1](data)

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Afit_transform

Bfit

Ctransform

Dpredict

Attempts:

3 left

💡 Hint

Common Mistakes

Using fit alone which does not return transformed data.

Using predict which is not a method for UMAP.

fit_transform fits the model and returns the reduced data in one step.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps each word to its length if length is greater than 3.

ML Python

{word: [1] for word in words if [2]

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Alen(word)

Blen(word) > 3

Cword.startswith('a')

Dword.isalpha()

Attempts:

3 left

💡 Hint

Common Mistakes

Using word.startswith('a') which filters words starting with 'a' instead of length.

Using word.isalpha() which checks if word has only letters.

The dictionary maps words to their lengths only if the length is greater than 3.

5fill in blank

hard

Fill all three blanks to create a dictionary of embeddings where keys are uppercase words, values are the first component of embedding, and only include if the first component is positive.

ML Python

{ [1]: embedding[i, 0] for i, [2] in enumerate(words) if embedding[i, 0] [3] 0 }

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Aword.upper()

Bword

C>

D<

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' instead of '>' in the condition.

Using 'i' instead of 'word' in the loop unpacking.

The dictionary keys are uppercase words, values are the first embedding component, filtered to positive values.