How to Learn Maths in ML/AI? | 35/100 Days of Python Algo Trading

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If you’re here, it means you’re truly dedicated to mastering Python. Directly below, you’ll find a quiz designed to help you reinforce what you’ve just learned. This isn’t just about recalling facts; it’s about deeply understanding the concepts. Take a moment to answer the questions and see how well you can apply the knowledge from the video. You’re doing great—every question you tackle brings you one step closer to becoming a Python expert!

Day 35: How to Learn Maths in ML/AI?

1. Which Python library is most commonly used for importing data from various sources like CSV, Excel, JSON, and SQL?

A) NumPy

B) Pandas

C) Matplotlib

D) Scikit-learn

2. When importing data from a CSV file using Pandas, which method would you use?

A) pd.read_excel()

B) pd.read_json()

C) pd.read_csv()

D) pd.read_sql()

3. To export a DataFrame to an Excel file in Pandas, which method is appropriate?

A) df.to_csv()

B) df.to_excel()

C) df.to_json()

D) df.to_sql()

4. Which library in Python is most effective for web scraping to gather data?

A) BeautifulSoup

B) NumPy

C) Matplotlib

D) TensorFlow

5. When gathering data through an API, which Python library is commonly used to handle HTTP requests?

A) urllib

B) httplib

C) requests

D) socket

6. In a data analysis process, what is the first step typically performed after data collection?

A) Data cleaning

B) Data visualization

C) Data modeling

D) Data exporting

7. To read data from a JSON file into a Pandas DataFrame, which method is used?

A) pd.read_csv()

B) pd.read_excel()

C) pd.read_json()

D) pd.read_sql()

8. Which Python library provides functions for reading and writing SQL databases?

A) Matplotlib

B) Seaborn

C) Pandas

D) TensorFlow

9. When exporting data to a CSV file in Pandas, which parameter ensures that the index is not written to the file?

A) index=True

B) index=False

C) header=True

D) header=False

10. Which method in Pandas allows you to fetch data from a SQL database and store it in a DataFrame?

A) pd.read_sql_query()

B) pd.read_sql_table()

C) pd.read_sql()

D) pd.read_sqlite()

11. In the context of web scraping, what is the primary purpose of using the BeautifulSoup library?

A) Making HTTP requests

B) Parsing HTML and XML documents

C) Handling web sockets

D) Managing databases

12. Which Python library is commonly used alongside BeautifulSoup for making HTTP requests?

A) urllib

B) requests

C) sockets

D) json

13. To clean data in a DataFrame by removing missing values, which Pandas method is used?

A) df.dropna()

B) df.fillna()

C) df.isna()

D) df.notna()

14. Which data format is best suited for exporting hierarchical data structures?

A) CSV

B) Excel

C) JSON

D) SQL

15. For large-scale data analysis, which data storage format is most efficient for compression and speed?

A) CSV

B) JSON

C) Parquet

D) Excel

16. When gathering financial data through an API, which endpoint parameter is essential for filtering data by date?

A) apikey

B) start_date

C) limit

D) symbol

17. To merge two DataFrames in Pandas based on a common column, which method is used?

A) pd.concat()

B) df.merge()

C) df.append()

D) df.join()

18. In data analysis, what is the primary purpose of data visualization?

A) To clean data

B) To model data

C) To explore and understand data patterns

D) To store data

19. When exporting data from a DataFrame to a SQL database, which Pandas method is used?

A) df.to_csv()

B) df.to_excel()

C) df.to_json()

D) df.to_sql()

20. Which Python package is commonly used for accessing and exporting data to Microsoft Excel files?

A) openpyxl

B) json

C) requests

D) BeautifulSoup

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