Python for Data Science and Machine Learning

Python for Data Science and Machine Learning - Important Points

1.		Which library in Python is commonly used for numerical computing and data analysis?

A. NumPy

B. Matplotlib

C. Scikit-learn

D. TensorFlow

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Answer: option a

Explanation:

NumPy is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays.

2.		Which library in Python is used for visualization of data?

A. Pandas

B. NumPy

C. Matplotlib

D. Scikit-learn

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Answer: option c

Explanation:

Matplotlib is a plotting library for the Python programming language and its numerical mathematics extension NumPy.

3.		Which library in Python is used for machine learning?

A. Pandas

B. NumPy

C. Scikit-learn

D. TensorFlow

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Answer: option c

Explanation:

Scikit-learn is a free software machine learning library for the Python programming language. It features various classification, regression and clustering algorithms including support vector machines, random forests, gradient boosting, k-means and DBSCAN.

4.		Which library in Python is used for deep learning?

A. Keras

B. PyTorch

C. TensorFlow

D. All of the above

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Answer: option d

Explanation:

Keras, PyTorch and TensorFlow are all popular libraries for deep learning in Python.

5.		What is the purpose of Pandas library in Python?

A. Data visualization

B. Data analysis

C. Deep learning

D. Machine learning

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Answer: option b

Explanation:

Pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, built on top of the Python programming language.

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