In this day and age, the aim to automate and enhance human-related tasks with the help of computers is the first focus.


At the current date, it is mainly performed through artificial intelligence (AI) and machine learning (ML).

These topics may seem intricate at first, especially if you’re just a freshman in the field.

But, in reality, it is not that difficult to delve into this section of data science. All you need is practice.

And, to practice your machine learning skills, you need to train your programs with data. Luckily, plenty of databases are available on the Internet for free. Yet still, you may be confused about where to begin and which of the thousands of machine learning datasets to select for the best assignment help.

So, to help you get done quickly, we have selected the ten best free datasets for machine learning projects ensuring that it covers all main topics of machine learning. Moreover, the tasks get progressively more complicated as you go through the list. This way, you can gradually improve your skills with practice.


Here are the top 10 public datasets for machine learning:


  1. Boston House Price Dataset

The Boston House Price Dataset involves the house prices in the Boston area developed on several factors, like several rooms, area, crime rates and many others. It is a perfect starting grid for machine learning beginners to search for easy machine learning projects since you can practice your linear regression skills for predicting the price of a specific house. It is also a viral machine learning dataset, so if you get stuck, you can find a lot of helpful resources about it online.

  1. Iris Dataset

The Iris dataset is suitable for linear regression and, thus, for beginner machine learning projects. It consists of information about the sizes of various parts of flowers. All these sizes are numerical, which makes it easy to begin and needs no preprocessing. The aim is pattern recognition — categorising flowers based on different sizes.

  1. MNIST dataset

The MNIST dataset is one of the most popular datasets in Machine Learning. It has over 70,000 labelled images of handwritten digits (0–9). 60,000 of those are placed in the training set and 10,000 in the test set. The images are sized at 28×28 pixels, and are heavily sanitised and preprocessed, sparing you to work on much of preprocessing.

Designed with preprocessing, this makes it very easy to use and fast, to begin with. In addition, this dataset allows the smooth functioning of many different models. So, as a beginner, you can use the straightforward linear classifier. However, you can also try and work on a deeper network. Given that the input is images, this is the best playground for learning Convolutional Neural Networks (CNN).

  1. Dog Breed Identification



Dog Breed Identification is entirely in the Computer Vision field. It is a dataset of images of different dog breeds. Your purpose is to develop a model that, given an illustration, can accurately foretell what its breed is.

  1. ImageNet

ImageNet is one of the best Machine Learning datasets centred on Computer Vision. It has 1,000+ classes of objects or people with many images linked with them. It even conducted one of the biggest ML challenges — ImageNet’s Large-Scale Visual Recognition Challenge (ILSVRC), which gave birth to many modern state-of-the-art Neural Networks.

  1. Breast cancer Wisconsin diagnostic dataset

The Breast Cancer Wisconsin diagnostic dataset is another exciting machine learning dataset for categorising projects is the breast cancer diagnostic dataset. Its design is based on the digitised image of a fine needle aspirate of a breast mass. In this digitised image, the characteristics of the cell nuclei are structured. For each cell nucleus, ten real-valued features are calculated, i.e., radius, texture, perimeter, area, etc. There are two types of predictions — benign and malignant. This database has 569 instances which consist of 357 benign and 212 malignant.

  1. Amazon Reviews Dataset

It is a Natural Language Processing (NLP) recommended for more advanced machine learning enthusiasts.

The Amazon Review Dataset consists of reviews (ratings, text, helpfulness votes), product metadata (descriptions, category information, price, brand, and image features), and links (also viewed/also bought graphs). The data spans more than 20 years of reviews.

  1. BBC News



Continuing with NLP, here we have text classification or more precise news classification. So, to develop your news classifier, you must have a standard dataset. For example, the BBC News dataset consists of more than 2,200 articles in different categories, and it is your job to try and classify accounting homework help.

  1. YouTube Dataset

Now we have arrived at an even more complicated topic — video classification—the YouTube dataset containing evenly sampled videos with high-quality labels and annotations.

  1. Catching Illegal Fishing

This final dataset for machine learning projects is for the experts.

There are many ships and boats in the oceans, and it is impossible to record what everyone is doing manually. That is why it has been advised to design a system that can point out illegal fishing activities through satellite and Geolocation data. So with the Catching Illegal Fishing dataset, The Global Fishing Watch offers actual-time data for free that can be used to build the system.


Final Thoughts

I have tried to include convincing data sets for all skill levels and various sections of machine learning research; however, there might be other, more specific datasets that also work for you.


Author Bio: Bella Evans is the CEO of a machine learning company in the UK. she also supervises the artificial intelligence evaluative essay help service of