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Last updated: May 20, 2022

Data Mining

Data mining is the practice of analyzing large databases to generate new information from them. It is also uncovering the patterns or hidden data from the given databases and analyzing them. It combines statistical and artificial intelligence to analyze these large data sets which we obtain using various techniques and then discover useful information from these. Using data warehousing and the growth of big data, and other such techniques of data mining helped in transforming the raw data into useful knowledge. It involves the discussion of various data mining techniques and architectures.
What Is Data Mining? MEDIUM
This article will take you through Data Mining, its importance, and the different tasks, advantages, disadvantages, limitations, and applications of data mining.
Data Mining vs AI EASY
In this article, we will first discuss data mining and Artificial Intelligence with their types, pros, and cons. Then the difference between data mining and AI.
Data Mining vs Text Mining
This article will cover all the related points covering data mining vs text mining. We will discuss data mining and text mining and then move to the differences.
Data Mining vs Machine Learning EASY
In this article, we will cover the differences between data mining and machine learning.
Data Mining vs Big Data
In this article, we will cover the difference between data mining and big data. We will start our discussion by understanding data mining and big data.
Scope of Data Mining EASY
This blog introduces data mining, its scope, and its benefits.
Author Aditi
0 upvotes
Outlier Analysis in Data Mining EASY
This article will take you through the concepts, techniques, practical applications, and a code example of outlier analysis in data mining.
FP Growth in Data Mining MEDIUM
In this blog,  we will study the working of FP algorithms in detail, along with their advantages and disadvantages.
The Data Mining Process EASY
This article on Data Mining Process Covers Data Mining Models, Steps and Challenges Involved in the Data Extraction Process.
Data Mining Architecture EASY
This blog explains the Data Mining Architecture and Its Components.
Discretization in Data Mining EASY
In this blog, we will learn about Discretization in Data Mining. We will understand its core concepts, its usage, advantages, and much more for better understanding.
Data Mining vs Web Mining EASY
In this blog, we will be discussing the features and applications of Data Mining and Web Mining followed by the differences between them.
Data Mining vs Data Snooping
In this article, we will first discuss data mining and data snooping with their types, pros, and cons. Then the difference between data mining and data snooping.
Data Mining vs OLAP EASY
In this blog, we will be discussing the features and applications of Data Mining and Olap followed by the differences between them.
Data Mining vs Deep Learning
In this article, we will first discuss data mining and deep learning with their types, pros, and cons. Then the difference between data mining and deep learning.
Data Mining vs Data Profiling
In this blog, we will be discussing the features and applications of Data Mining and Data Profiling followed by the differences between them.
Types Of Data Mining Architecture EASY
In this article, we will learn about Data Mining Architecture, its types, advantages, and disadvantages.
​​Bayesian Classification in Data Mining EASY
This article explains the Bayesian Classification in data mining. It involves predicting a class label for a given input by utilizing probability theory.
Data Cube in Data Mining EASY
This guide aims to simplify and explain data cubes, their significance, and how they're used in data mining.
KDD in Data Mining EASY
KDD is a method of extracting relevant, unknown, and useful data from massive databases(also known as big data).
Outlier Detection in Data Mining EASY
In this blog, we will learn about the different methods of Outlier Detection in Data Mining, along with their application and challenges.
Detecting Phishing in Data Mining MEDIUM
In this article, we will discuss what Phishing is, the method of detecting phishing in Data Mining, along with the Random Forest Algorithm.
Data Mining Vs Data Analytics EASY
This blog explains the detailed difference between Data Mining and Data Analytics.
Fake News Detection Project in Data Mining MEDIUM
This article will discuss the problem of fake news circulation in social media and its possible solutions using fake news detection project in data mining.
What is Regression in Data Mining? EASY
This article will discuss Regression in data mining and types of regressions in detail, along with their equations and graphs and some applications of Regression.
Data Mining Vs Data Warehousing EASY
This blog contains an introduction to data mining and data warehouse and their differences.
Author Aditi
0 upvotes
Applications of Data Mining
This article on Applications of Data Minings Covers Data Mining and its applications in various fields.
Credit Card Fraud Detection Project in Data Mining MEDIUM
This article covers the concept of credit card fraud detection project in data mining with its implementation.
Clustering in Data Mining MEDIUM
Clustering is a technique in data mining that groups similar data points together based on their features and characteristics. This article will teach you all you need to know about clustering in data mining

Data Mining Techniques

There are various methods and technologies, because of which it becomes a priority to know how to process data and make predictions and conclusions on the basis of it. But again what methods can be used for all this processing? What do you think? Let's see what are the data mining techniques? Starting with the introduction to it, where we will introduce various techniques. Then we will take up each of them individually and explain each of them with proper explanation to you. It includes classification, clustering, regression, association, and outlier detection.
Types of Data Mining Techniques
In this article, we have explained basic data mining concepts and different types of data mining techniques.
Tasks and Functionalities of Data Mining MEDIUM
Data mining functions are utilized to identify trends and correlations within data mining operations.
Classification in Data Mining
In this post, we will discuss the basic concepts of the classification analysis technique of data mining.
What is Spatial Data Mining?
In this article, we will discuss Spatial Data Mining, its applications, types of Spatial Data and Spatial Vs Temporal Data Mining.
Partitioning Methods in Data Mining MEDIUM
In this blog, we will learn about Partitioning Methods in Data Mining. We will understand its core concepts, its usage, types, and much more for better understanding.
Association Rule Learning EASY
This article explains the rule of Association Rule Learning and how this technique is used in data mining and includes machine learning.
Multilevel Association Rule in Data Mining
In this article, we will talk about the Multilevel Association Rule in Data Mining. We will also see some algorithms and approaches used in this rule.
Author jay_03
0 upvotes
Anomaly detection EASY
This article explains Anomaly detection or outlier Detection and how this can be used in data mining using machine learning.
Regression Analysis EASY
This article will take you through the introduction, importance, and the types of Regression Analysis.
Rule-Based Classification in Data Mining MEDIUM
This article will cover the topic of rule-based classification in data mining.

Data Mining Tools

After knowing about the techniques of data mining, the next stop is the machine or tool where we can execute the data mining techniques. Data mining tools are like R-studio or tableau where you can frame and execute the data mining techniques, thus creating the data models and also text these models. there are many open source and sophisticated tools. In this, we will be looking at some of them. But before that, we need an introduction to these data mining tools and many more than that. After that introduction, we will take up some of them and discuss them. Here we will be discussing - Rapid Miner, Python, orange, and kaggle.
Tools in Data Mining
In this article, we will learn about various data mining tools. We will also understand the meaning and implementation of data mining.
Rapid Miner EASY
This article will give you a brief overview of the data mining tool– Rapid Miner.
Python in Data Mining EASY
In this article, we will learn how Python is used in various data mining applications.
Orange in Data Mining EASY
This blog mainly focuses on the Orange data mining and data visualisation tool, usage of the Orange, and different features available in Orange.
Oracle Data Mining
In this article, we will learn about Oracle Data Mining. We will also learn about Oracle Data Miner and its features. We will see the various functions and advantages of Oracle Data Mining.
Kaggle EASY
This blog mainly focuses on the concept of Kaggle. We will discuss what the Kaggle is, the importance of the Kaggle in data science, Kaggle competitions, Kaggle datasets, Kaggle notebooks and Kaggle public API.
Introduction to Weka
This article is about Weka and its features, installation process, Weka for data mining and machine learning, and real-life applications.