With the world rapidly advancing in technology, data mining has become one of the most crucial fields for innovation. To start off working in this modern space of science, working on data mining projects could be the best! Here are some of the data mining project ideas for the people who look forward to excelling in data-mining.

  •  Behavioural Constraint Miner:

One of the most common data mining projects for beginners, this is a sequence classification project that deals with extracting sequential patterns in the data sets. This project can help to predict a variety of behavioural patterns over the sequence helping users to derive conclusions.

  • Fake News Detection:

This data mining project in Python is aimed at determining whether the news reported is fake or real. The performer will have to use Python classifiers to successfully complete this data mining project.

  • Group Event Recommendation:

This data mining project is a solution for recommending the social events which include exhibitions, concerts, plays, talks, concerts, etc. It uses special algorithms to derive out the group preferences and can use additional contexts.

  • Detection of Parkinson’s Disease:

Parkinson’s disease is a typical condition that people are affected by growing age. Data mining techniques can be used for extensive classification of medical data. The data mining project uses algorithms for the development of classifiers to distinguish between a normal and affected person.  

  • Protecting user data on social networks:

Data on social sites is sensitive and should be protected from online predators. Data mining ideas provide solutions that use special encryption methods and multiple servers that can help to preserve data.

  • Detecting websites involved in phishing:

This data mining project uses ideas like logistic regression and decision trees to help detect malicious phishing websites. This project uses Python language for the implementation. 

  • Personality Classification project using data mining:

This data mining project is used for testing the personality traits of the users. Performers can first store the major data related to all personality types in the form of data sets. After the collection of significant features from the user, the next step is to relate it to the data set to come up with a concussion about the person’s persona.

  • HandWritten digit recognition:

This data mining project uses one of the most widespread datasets called the MNIST dataset to develop a model for identifying handwritten digits.

  • Diabetes Prediction using data mining:

Using data mining algorithms like Decision tree, Naive Bayes, SVM calculations, this data mining project for beginners is used to know whether any person has diabetic symptoms or not.

  • Intelligent Transportation System:

This simple data mining idea is used to forecast optimized routes for transportation, analyse passenger data and find out the number of vehicles required for the purpose all using data sets.

  • Sentiment Analysis:

The data mining project uses R-programming language to model out an algorithm which helps to analyse and categorize words as positive, negative or neutral.

  • Credit Card Fraud:

This data mining project using python uses the previously available data and datasets to predict whether there has been a fraud or not.

  • Tourism:

The TourSense project in data mining uses a graph-based iterative propagation learning algorithm to identify tourist behaviour and predict their details of the next tour.

  • Customer Segmentation:

Splitting of customers into various categories is a necessity nowadays. This data mining project uses clustering algorithms of data mining to partition the customers in various categories. 

  • Speech Emotion Recognition:

The data mining project for cse uses python language to store significant features of speech and emotions in the form of datasets. By using Vox Celebrity Dataset, the project relates the speech to the data in the dataset.

  • Predictive Analysis:

The data mining project is used to predict unknown events of the future using statistical modeling.

  • Regression Analysis:

It is used to derive probabilistic conclusions about any event by analysis of historical data. Data trees and linear regressions are some data mining algorithms which must be used. 

  • Exploratory Data Analysis:

This is the first step in the data analysis process. This data mining project is focussed to study the data you have and use algorithms to manipulate it according to needs. 

  • House Price Prediction:

This data mining project based on machine learning uses basic ML algorithms to predict prices of real estates.

  • Movie Recommendation:

Using historical data of the users, this idea of the data mining project is used for recommending movies using clustering algorithms and other mathematical functions in Python.


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