Data Science and Machine Learning (Theory and Projects) A to Z - Implementation of DNN for COVID 19 Analysis: COVID19 Da

The video tutorial demonstrates data analysis techniques on a coronavirus dataset from Kaggle, covering data preparation, grouping, and visualization of trends in confirmed, recovered, and death cases across various countries. The analysis highlights trends in specific countries and globally, using tools like pandas, Matplotlib, and Numpy.

What is the source of the coronavirus dataset used in the video?

• Johns Hopkins University

• CDC

• World Health Organization

• Kaggle

How many countries' data is included in the dataset up to 16th March?

• 200

• 171

• 150

• 220

Which library is used for plotting the data in the analysis?

• Matplotlib

• Bokeh

• Seaborn

• Plotly

What method is used to handle missing values in the dataset?

• Dropping missing values

• Imputing with a fixed constant

• Using mean substitution

• Filling with zero

What is the first step in preparing the dataset for analysis?

• Loading the dataset using pandas

• Exporting the dataset

• Cleaning the dataset

• Visualizing the data

Which country showed a significant increase in confirmed cases after 40 days?

• Canada

• Australia

• Brazil

• Belgium

Which country was noted for having a high recovery rate despite growing confirmed cases?

• India

• Hong Kong

• Iran

• Italy

What trend was observed in France's confirmed cases in the last 10 days of the dataset?

• Rapid increase

• Stable

• Decreasing

• No change

What was the overall trend in confirmed cases worldwide by 16th March?

• Stable

• Fluctuating

• Decreasing

• Increasing

What is the hope expressed regarding the death rate in the global trend analysis?

• It will remain slow

• It will increase

• It will decrease rapidly

• It will fluctuate