Data Mining Projects
Explore the latest and trending Data Mining Projects with source code to strengthen your skills in the domain. Enroll in this course today and learn to develop solutions for real-time data mining problems through working projects.
What you learn in Data Mining Projects ?
About this Free Certificate Course
This Data Mining Projects course is designed to engage you with the best way to learn data mining. This course demonstrates projects on IPL Data Analysis and COVID Analysis to give you a headstart for developing applications on Data Science and to increase your visibility through your resume, and improve your skills to crack interviews. These projects guide you to learn the concepts better. These projects will be executed in Python programming language. Libraries such as pandas, Matplotlib, and Seaborn will be used to perform EDA on the projects. Take up the quiz to complete the course and avail the certificate.
You can enroll in the Data Science courses after this free, self-paced, beginner's guide to Data Mining Projects to embark on your career. Learn and earn a Post-Graduate Certificate with millions of aspirants across the globe!
Course Outline
Our course instructor
Mr. Bharani Akella
Data Scientist
With this course, you get
Free lifetime access
Learn anytime, anywhere
Completion Certificate
Stand out to your professional network
1.5 Hours
of self-paced video lectures
Frequently Asked Questions
What are the prerequisites to learning this Data Mining Projects course?
This is a beginner’s course and includes a comprehensive guide to help you learn to work with data mining projects with source code. But, you will have to do a little homework to learn Python programming language since the projects are run through it and machine learning before you dive into learning this course.
How long does it take to complete this free Data Mining Projects course?
Although Data Mining Projects is a 1.5-hours long course, you can learn it at your leisure since it is self-paced.
Will I have lifetime access to this free Data Mining Projects online course?
Yes. Once you enroll in this free course to learn Data Mining Projects with source code in Python, you will have lifetime access to it.
What are my next learning options after this Data Mining Projects course?
After you have completed this course, you can either learn other concepts in Data Science and Big Data individually, or you can register for the best Data Science programs and master them all under a single roof.
Why is it essential to learn Data Mining Projects?
Data mining is a composite discipline that can represent a variety of methods or techniques used in various analytical methods that assist businesses and organizations in making profitable business decisions. They do this by asking different kinds of questions and using different degrees of user input or rules to come to a conclusion. Data mining projects helps you have a better hold through helping you practice different concepts through working on practical examples and projects, hence making it essential to learn.
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Data Mining Projects
Data Mining is the procedure of extracting useful information for the identification of the patterns of large-scale data sets. We extract the information from the data itself. Data mining is very useful for finding valuable information from large volumes of data. We find patterns, regularities, irregularities in sets of data using Data Mining. The data which is collected and stored in particular areas like data warehouses databases are investigated in data mining for the categorization of useful and useless data. Data mining is used in organizations to solve data-related problems by turning the raw data into useful data. Data mining is related to the term Data Science because, in Data Science, various operations are done on the data, and the data is collected through Data Mining. For mining the data, there are various techniques and software available in the market which are very useful.
Types of Data Mining:
Data Mining is done in multiple processes. Data Mining can be performed on different types of Data which are as follows:
1. Relational Database: In relational databases, the data is organized in the form of tables and records that can be accessed in multiple ways, such as by recognizing the database tables. Data Mining can be done in relational databases for extracting useful information using some techniques of the database.
2. Object-Relational Database: The object-relational database consists of the data in which all the data is treated as objects. In other words, we can say the Object-Relational Database is the combination of Object-oriented Database Model and Relational database model. Therefore the data which is stored in this database consists of data of both types.
3. Data Warehouse: Data Warehouse is just like a godown where we store all our data. A data warehouse is utilized to store the data which we just extracted with the help of Data Mining. Also, we can perform Data Mining in Data Warehouse.
4. Transactional Database: It contains the data related to the transactions done in the database. The transactional data can be extracted using Data Mining for only useful transactions.
Tasks of Data Mining:
Data Mining technique is used widely in various tasks which includes the following:
- Classification of Data: In this task, the data is classified in data mining. Classification algorithms are used to classify different types of data.
- Prediction: The next task of data mining is a prediction which means data mining can be used for prediction purposes. What data mining actually does is it extracts the data and classifies it, then it is used in supervised learning to predict various things related to the customer base in the future, raining scale, etc.
- Regression: In this task, the regression technique is used to find the relationships in the tables/graphs where x and y coordinates define different values at different times.
- Time-series Analysis: In time series analysis, data mining is useful to determine the continuously changing values of the variables. It is used to identify the variable value which changes in specific time series.
- Clustering: We just discussed Classification, and clustering is the same as classification in which different types of data are clustered, and the same kind of data is grouped together.
- Characterization and Discrimination: Data Characterization means characterizing the general rules of the objects in the target class. And Data Discrimination is responsible for the creation of this series of rules. Data Mining is very helpful in both of the tasks.
- Summarization: Summarization is the same as Characterization and Discrimination in which generalization of meaningful data is made. The summary is the result after the completion of the task, which will be retrieved as a result through Data Mining.
- Association Rules: In this task, the appropriate patterns and useful insights are extracted from the database. It is a type of data model which is used for extracting data associations.
- Evolution & Analysis of Deviation: In this task of Data Mining pattern discovery, time-series results, periodicity, and similarities in patterns are analyzed.
- Sequence Discovery: In this task, the sequential pattern in the data can be found using data mining. The sequential pattern of the data means the data is in different sequences of time, and it can be discovered using Data Mining.
Data Mining Projects:
There are a number of various projects on Data Mining that you can work with. Most of the data mining projects are done in Python. You can start learning about these projects online, where you will find the source code too. Data Mining projects are very helpful if you do work on any project and add them to your portfolio to get a job. We will see some useful and best data mining projects here.
- Credit Card Fraud Detection: As we see in our daily life, credit card fraud is increasing day by day. With the increase in online payments and transactions, these kinds of fraud risks are on the rise. And Data Mining comes into view to detect if the Credit Card entered by the user for the payment is correct or not. Data Mining is used to verify the data entered by the user if it is correct or not. Python is used for this project in which we will classify the valid data available in the databases and try to validate it with the data entered by the user.
- Heart Disease Prediction: This project is really helpful for detecting if the patient is suffering from Heart Disease or not. In this project, all the information related to health about the patient is provided to the data model, and then our data model will do the analysis and predict the results. As health issues are increasing at this time, this project is very beneficial in medical sciences.
- Fake News Detection: We hear a lot of news in our day. Some news is true, and some are fake. But it is very difficult to choose which news is true or real and which one is fake. In this project, we will create a data model which will detect which news is fake based on some information and analysis. This can be one of the best projects of data mining.
- Diabetes Prediction: As we already discussed in the project Heart Disease Prediction, we will use the same strategy in this project too. We will provide the patient's details to the data model we created using python, and it will analyze the information and give the results if the patient has diabetic symptoms or not.
- Pattern Mining: This project is the main project in data mining in which the different kinds of information are categorized by analyzing the pattern in the data. The raw data is used for extraction, and useful data will be separated into results. In pattern mining, the data model finds the different types of patterns in the data we provided. This project is helpful in obtaining the information related to a customer base in organizations.
- Sentiment Analysis: Emotional Analysis can also be done using Data Mining. This project is very useful. In this project, the data from the user is taken as input and verified from different sets of data available using the data model. After that, our data model will give the results if the person is happy, emotional, or angry based on the information he provided.
Mini Data Mining Projects Ideas:
You have plenty of options to start doing projects in Data Mining, and all these options are very helpful and innovative. By doing real-life projects, your knowledge will increase rather than just doing the theoretical stuff. This course is specially designed for those who are beginners in Data Mining. Let us see the list of ideas of Mini Data Mining Projects Ideas below:
- House Price Prediction
- Movie Recommendation System
- Handwritten Digit Recognition
- Intelligent Transportation System
- Behavioural Constant Miner
- Group Event Recommendation
- Personality Classification Project
- Crime/Fraud Detection System
- Online Rating for Product System
- Products Recommendation System for E-commerce
- Web mining for security
- Text Mining on Websites
- Mining of Customer Behaviour
- Mining of valuable information from government sites