What are Datasets? Let's See!
A dataset is a collection of data in which data is arranged in some order. A dataset can contain any data from a series of an array to a database table. A tabular dataset can be understood as a database table or matrix, where each column corresponds to a particular variable, and each row corresponds to the fields of the dataset. The most supported file type for a tabular dataset is "Comma Separated File," or CSV. But to store a "tree-like data," we can use the JSON file more efficiently.
Types of data in datasets Let's Understand!
● Numerical data : Such as house price, temperature, etc.
● Categorical data : Such as Yes/No, True/False, Blue/green, etc.
● Ordinal data : These data are similar to categorical data but can be measured on the basis of comparison.
● Time Series Data
Need of Dataset Let's See!
To work with machine learning projects, we need a huge amount of data, because, without the data, one cannot train ML/AI models. Collecting and preparing the dataset is one of the most crucial parts while creating an ML/AI project. The technology applied behind any ML projects cannot work properly if the dataset is not well prepared and pre-processed. During the development of the ML project, the developers completely rely on the datasets. In building ML applications, datasets are divided into two parts:
● Training datasets
● Test Dataset
Resources for Datasets :-
● Kaggle Datasets
● UCI Machine Learning Repository
● Datasets via AWS
● Google's Dataset Search Engine
● Microsoft Datasets
● Awesome Public Dataset Collection
● Government Datasets
● Computer Vision Datasets
● Scikit-learn dataset
