Data Types
Key terms in ML
Data Visualization and Hypothesis
Data and Analysis
Null and Alternative Hypotheses
100

Give an example of semi structured data type.

XML, JSON files

100

What is Model Assessment?

Evaluation of a model's performance using parameters like accuracy, precision, and recall.

100

When an hypothesis is formulated, ___________ is the next step?

Hypothesis testing

100

_________ uses visuals to communicate insights from data.

Data Storytelling

100

Why is testing important in null hypothesis?

It aims to confirm or reject the null hypothesis.

200

What is 'Time Series' in data types?

It is collected over a long period of time.

200

What does model training help in?

It helps the model to make decisions which are more accurate and meaningful.

200

What is the benefit of data visualization?

It provides an accessible way to see and understand tends, outliners, and patterns in data.

200
__________ is a statistical method used to determine if a result is due to a chance or it is statistically significant.

Significance Testing

200

What are P-values?

It evaluates how likely results are due to chance.

300

What is the data type of spreadsheets, databases?

Structured

300

What does regression algorithm predict with example?

It predicts continuous values like prices.

300

Which library is used for data visualization?

matplotlib.pyplot

300

What is the formula for Accuracy?

Accuracy = (Correct predictions)/(Total Predictions)

300

'Coffee has no effect on productivity', which hypothesis is this?

Null hypothesis

400

It can automatically learn patterns from data without explicit programming. What is it?

Machine Learning

400

________ algorithms group similar data points together.

Clustering
400

'Increased study hours lead to better exam scores for students', which is the independent variable in the hypothesis?

Study Hours

400

____________ is the process of making an educated guess, or assumption about a relation between variables based on existing data or prior knowledge.

Hypothesis Formulation

400

What is 'Type II Testing'?

Failing to reject when it is actually false.

500

What happens after data preprocessing?

A suitable machine learning algorithm is chosen based on the problem at hand.

500

What is the formula for Precision in Machine learning?

Precision=(True Positives)/(True Positives + False Positives)

500

Give an example of a language that helps us get data from databases.

SQL

500

____________ is the harmonic mean of Precision and Recall.

F1 Score

500

P-values means strong evidence against the ______ hypothesis.

Null