Before diving into data mining projects, we need to understand their importance. Data is the most powerful weapon in today’s world. With technological advancement in the field of data science and artificial intelligence, machines are now empowered to make decisions for a firm and benefit them.
Here is where data mining comes into the picture. This technique helps businesses and firms to analyze valuable user data to their benefit. According to Glassdoor, the average salary of a Data Mining Engineer in the US is around $115,000. But what is the best way to practice way?
Here we present 15 interesting data mining project ideas for students that they can make for their final year as well. So let’s get Started!
What is Data Mining?
The method of extracting useful information to identify patterns and trends in the form of useful data that allows businesses and huge firms to analyze and make decisions from huge sets of data is called Data Mining.
In layman’s terms, Data Mining is the process of recognizing hidden patterns in the information extracted from the user or data which is relevant to the company’s business. This is passed through various data-wrangling techniques.
We categorize them into useful data, which is collected and stored in particular areas such as data warehouses, efficient analysis, and data mining algorithms, which help their decision-making and other data requirements which benefits them in cost-cutting and generating revenue.
It is not an easy subject to understand in university when there is always so much more work to be done. You can get expert data mining help online now for instant doubt-solving.
Data Mining Project Ideas for Students
While there are many beginner-level data science projects available, we select some of the best project ideas for students that they can build to either showcase it on their resume or make it for their final year submission:
1) Fake news detection
With the advent of the technological revolution, it is easier for users to have access to the internet which increases the probability of fake news to spread like a wildfire. You will learn how to classify news into Real or Fake in this project.
It is one of the new ideas for data mining projects which is quite popular among students. You will use PassiveAggressiveClassifier to perform the above function.
2) Detecting Phishing website
In recent times, technological advancement created a way for the development of e-commerce sites and most of the users started shopping online for which they have to provide their sensitive information like bank details, username, password, etc.
Fraudsters and cybercriminals use this opportunity and create fake sites that look similar to the original to collect sensitive user data. In this data mining project, you will develop an algorithm to detect phishing sites based on the characteristics like security and encryption criteria, URL, domain identity, etc.
3) Diabetes prediction
Diabetes is one of the most common and hazardous diseases on the planet. It requires a lot of care and proper medication to keep the disease in control. This data mining project, this project teaches you to develop a classification system to detect whether the patient has diabetes or not.
As part of this project, you will learn about the Decision tree, Naive Bayes, SVM calculations, etc. Find the dataset here.
4) House price prediction
In this data mining project, you will utilize data science techniques like machine learning to predict the house price at a particular location. This project finds applications in real estate industries to predict house prices based on previous data.
The data can be =the location and size of the house and facilities near the house. This data mining project is an evergreen topic in the USA. Find the dataset here.
5) Credit Card Fraud Detection
With the increase in online transactions, credit card fraud has also increased. Banks are trying to handle this issue using data mining techniques. In this data mining project, we use python to create a classification problem to detect credit card fraud by analyzing the previously available data.
We have made this credit card fraud detection project using machine learning here.
6) Detecting Parkinson’s disease
Data mining techniques are widely utilized in the healthcare industry to provide quality treatment by analyzing the patient’s medical records. Here you will learn to predict Parkinson’s disease using python. The project works with UCI ML Parkinson’s dataset. Find more information about the project dataset: here.
7) Anime recommendation system
This is one of the favorite data mining project ideas among students. An enthusiast in this field can easily get involved and excited by such topics.
This data set contains information on user preference data from 73,516 users on 12,294 anime. Each user is able to add anime to their list and give a rating and this data set is a compilation of those ratings. The aim is to create an efficient anime recommendation system based only on user viewing history. Find the dataset: here.
8) Mushroom Classification
This dataset contains details of hypothetical samples corresponding to 23 species of gilled mushrooms in the Agaricus and Lepiota Family Mushroom drawn from The Audubon Society Field Guide to North American Mushrooms (1981). Each mushroom species is identified as definitely edible, definitely poisonous, or of unknown edibility, and not recommended.
This latter category is combined with the poisonous one. The facts suggest that there is no simple rule to determine if the mushroom is edible; no rule like "leaflets three, let it be'' for Poisonous Oak and Ivy. Find more information about the data: here.
9) Solar Power Generation Data
This data has been extracted from two solar power plants in India over a 34-day period. It has two pairs of files: each pair has one power generation dataset and one sensor reading dataset. The power generation datasets are extracted from the inverter level; each inverter has multiple lines of solar panels attached to it.
And the sensor data is extracted from a plant level; a single array of sensors is optimally located at the plant. These are concerns at the solar power plant:
- Can we predict the power generation for the next couple of days?
- Can we identify the importance of panel cleaning/maintenance?
- Can we identify faultily or suboptimally performing equipment?
The dataset: here.
10) Heart Disease Prediction
Heart disease is one of the most common diseases. It needs a lot of care from the doctor to get diagnosed. In this data mining project, you will learn to develop a system to detect whether the patient is suffering from heart disease or not. In this project, you will learn about the Decision tree, Naive Bayes, SVM calculations, etc.
This data mining project is quite difficult than others but it will surely add a lot of credibility to your knowledge of the subject. Find the dataset: here.
11) Fraud Detection in Monetary Transactions
Detecting fraudulent transactions is a very significant use case in today’s scenario of digitized monetary transactions. In order to address this problem, Synthetic Data is generated using PaySim Simulator and it is made available at Kaggle.
The data contains transaction details like transaction type, amount of transaction, customer initiating the transaction, old and new balance in Origin i.e., before and after transaction respectively, and same as in Destination Account along with the target label, is fraud.
o, based on the transaction details, a Classification Model can be developed that can detect fraudulent transactions.
12) Adult Census Income Prediction
The US Census Data is made available at the UCI Machine Learning Repository. The Dataset contains variables like age, work class, hours per week, sex, etc. including other variables that can foretell whether the annual income of an individual is greater than 50K dollars or not.
This is a Classification Problem for which a Machine Learning model can be trained to predict the Income Level of an individual.
13) Titanic Survival Prediction
In order to get started with Data Mining, this is the go-to project. A Titanic Dataset is created by Kaggle and a competition for the same is being hosted in this link. The data contains explanatory variables like Passenger details like Class, Gender, Age, Fare, etc.
These variables are responsible for predicting whether a passenger will survive the Titanic Disaster or not with Survived (0/1) as the target variable. So, the Project Expectation is to build a Classification ML Model that predicts the probable survival of the passenger in Titanic.
14) Air BNB Market Analysis
Analyzing the Air BNB market is pretty important for the company to figure out where the demand is and how to advertise to people. Using data mining algorithms, they can take a look at where customers are coming from, where properties are located, and how much they cost.
15) NBA Shooting Analysis
If you're just starting out in data analysis, looking at NBA shooting stats is a great way to practice. The stats include information about where players shoot from, where they're most likely to score, and how the defender affects the shot.
By using data mining algorithms, you can analyze all of this data to help coaches and players improve their games. Students will definitely love to make this data mining project because everyone likes NBA.
Applications of Data Mining
Here are some major applications:
- Financial Analysis: The banking and finance industry relies on high-quality and processed, reliable data. In the finance industry user, data can be used for a variety of purposes, like portfolio management, predicting loan payments, and determining credit ratings.
- Telecommunication Industry: With the advent of the internet the telecommunication industry is expanding and growing at a fast pace. Data mining can help important industry players to improve their service quality to compete with other businesses.
- Intrusion Detection: Network resources can face threats and actions of cybercriminals can intrude on their confidentiality. Therefore, the detection of intrusion has proved as a crucial data mining practice. It enables association and correlation analysis, aggregation techniques, visualization, and query tools, which can efficiently detect any anomalies or deviations from normal behavior.
- Retail Industry: The established retail business owner maintains sizable quantities of data points covering sales, purchasing history, delivery of goods, consumption, and customer service. Database management has improved with the arrival of e-commerce marketplaces and emerging new technologies.
- Spatial Data Mining: Geographic Information Systems and many other navigation applications utilize data mining techniques to create a secure system for vital information and understand its implications. This new emerging technology includes the extraction of geographical, environmental, and astronomical data, extracting images from outer space.
How do I Start a Data Mining Project?
The first thing you would need to do is define a problem statement. Your project is only as good as your problem statement. Once you have defined a problem statement, gather data to solve the problem statement.
The data needs to be properly cleaned and in the format that you require it to be. After you have the data, run the data mining algorithms and visualize the results. This can help you gain insights from the data and help in choosing appropriate models to train the data on.
Best Ideas for Final Year Projects
You can choose ideas like Fake News Detection, Heart Disease Prediction, and Air BNB Market Analysis for this your first data mining project. As we know that most students are making it to final year submission. These are very complex and require a lot of data and algorithms.
Not only will these projects expand your understanding but also your teachers or supervisors will also favor such topics that are more related to the current times.
Data mining is a composite discipline that can represent a variety of methods or techniques used in different analytic methods that helps firms and organizations to make efficient business decisions and benefit them.
Now you have the list of Data Mining projects for beginners. So what are you waiting for, select one and start working on it. Happy Learning :)