In the article, “Top 10 Python Libraries Data Scientists Should Know in 2022,” what libraries were SciKit-Learn designed from, according to the author? Why do you think the creator of SciKit-Learn used those libraries?

Discovery and learning with big data week 6
Instructions
Watch the YouTube video and read the two articles provided to answer the questions listed below. Ensure your answers are drawn primarily from the video and articles and cite your source for each question.
Next, download and open the Assignment 6 Hands-On ipynb file in your Jupyter Notebook and run through the three exercises.
Questions
In the YouTube video “Pandas for Data Science in 20 minutes,” what does the acronym CRUD stand for in the video?
In the YouTube video ” Pandas for Data Science in 20 minutes,” what were the data types in the telco_churn file?
In the YouTube video “Pandas for Data Science in 20 minutes,” the speaker used the describe method, list four of the results from the describe method for the variable “account length.” What is the purpose of the describe method?
In the article, “Top 10 Python Libraries Data Scientists Should Know in 2022”, name one of the four libraries not discussed in class. Should the professor include this library in future lectures? Why or why not?
In the article, “Top 10 Python Libraries Data Scientists Should Know in 2022,” what libraries were SciKit-Learn designed from, according to the author? Why do you think the creator of SciKit-Learn used those libraries?
The article, ” An overview and comparison of free Python libraries for data mining and big data analysis,” identify two of the least used data visualization libraries discussed in the article. Why do you think they are used the least?
In the article, “An overview and comparison of free Python libraries for data mining and big data analysis,” the author discusses several deep learning libraries. Which deep learning library list in the article would you want to use and why?

Hands-On
Use Jupyter Notebook to complete the Python exercises.
Download Series, DataFrames, NumPy Arrays.ipynb file that includes three exercises. Complete the exercises and save your work. Upload your ipynb and pdf files.

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