If you are a beginner in data science, then you must be confused about which datasets you should use for improving your data science skills. If you have never worked on any dataset before then you should only choose datasets that are meant for beginners. In this article, I will take you through the best datasets for data science beginners that you can use to improve your data science skills.
Best Datasets for Data Science Beginners
There are so many datasets available online for data science beginners. You can also find some of the datasets already available in Python libraries like Scikit-learn and Tensorflow. Below are some of the best datasets for Data Science beginners that you can try one by one.
The Iris dataset is one of the most popular datasets among the data science community. It contains the data about three Iris species; setosa, versicolor, and virginica. This dataset is based on the problem of classification where every iris belongs to one of the three species. So your task here is to classify the species of the flower. You can download this dataset from here, but as this is already included in the Scikit-learn library in Python so you can also import it using the code below:
from sklearn.datasets import load_iris iris_dataset = load_iris()
Another popular dataset among the data science community for beginners is the Classic Titanic dataset. This dataset contains data on demographic and travel information of Titanic passengers and our goal is to predict the survival of these passengers. This dataset is also based on the classification problem. You can download this dataset from here.
Stock Prices Dataset:
You can use the historical data of stock prices to predict the future prices of a company. You can use the same strategy to predict the prices of bitcoin. Predicting future prices is the problem of regression. To download such datasets follow the steps mentioned below:
- visit Yahoo Finance
- then search for any company, let’s say Apple
- Search for Apple and you will get to see the latest stock prices of Apple
- then click on Historical Prices
- and then click on download.
These steps will help you to download the stock price data for the past 365 days.
The MNIST dataset is so popular dataset among the data science community that it is also known as the hello world of machine learning. It contains 70,000 small images of handwritten digits where each image is labelled with the digit that it represents. This dataset is already available in the Scikit-learn library in Python. You can import it by using the code below:
from sklearn.datasets import fetch_openml mnist = fetch_openml('mnist_784', version=1)
So these were some of the best datasets for data science beginners. You can practice so much with these datasets. After working on these datasets you can start working on some more complex problems. You can find so many machine learning projects solved and explained based on complex problems from here. I hope you liked this article on the best datasets for Data Science beginners. Feel free to ask your valuable questions in the comments section below.