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In the example given below, we are comparing data gathered for measuring the weight of 12 eggs in a box in
grams.
Task #Creativity & Innovativeness
Open a website https://www.kaggle.com. Kaggle is like a playground for data enthusiasts!
It’s an online platform where people from all over the world come together to play with data,
learn new things, and compete in data science competitions.
Do this
The Titanic competition on Kaggle is a classic and beginner-friendly challenge that introduces you to the
basics of data analysis and machine learning. The goal is to predict whether a passenger survived the Titanic
shipwreck based on factors like age, gender, ticket class, and more.
Explore:
Kaggle provides tutorials and notebooks to help you get started with the Titanic competition. You can find
them under the "Notebooks" tab on the competition page.
Features of Data
Data features are also called the characteristics or properties of the data. They describe each piece of information
in a dataset. They define what each data point represents and help us make sense of the data. For example,
● In a table of student records, features could include things like the student’s name, age, or grade.
● In a photo dataset, features might include properties like the colour present in each image, the resolution,
brightness, or the presence of certain objects.
These features help us understand and analyse the data. In AI models, we need two types of features: Independent
and Dependent.
Independent
Independent variables (sometimes called predictor variables) are those that are used to generate predictions
about or to account for the variation in the dependent variable (the goal). These features are the input to the
model—they’re the information we provide to make predictions.
Dependent
The dependent variable is the variable about which predictions or explanations are being sought. These features
are the outputs or results of the model—they’re what we’re trying to predict. For example, imagine we’re
building an AI model to predict students’ final exam grades based on various factors.
Data Literacy 271

