Data Analyst is the most sought after job amongst today’s generation. Students get confused how to begin it with and what to do. The simple rule is to start with the fundamentals and try various algorithms and techniques practically. There are many tools available online for data mining, such as web scraping tools. They use machine learning, artificial intelligence, and other techniques for analyzing data. Few of them are:
It is the most fundamental tool for beginners. Waikato Environment for Knowledge Analysis(WEKA) is used for pre-processing, clustering, regression, association rules, classification and visualization. Those who have just started learning data mining would be easily able to perceive the analysis results. It is an open source software which comes under GNU General Public License.
For academic and research purposes, you should go for Tanagra. It is an easy-to-use user-friendly free software which contains many supervised & unsupervised learning algorithms. The drag-and-drop feature makes it feel like a child’s play.
RapidMiner is the #1 open source data platform as rated by various technical websites. It offers advanced analytics, through its integrated environment, including machine learning, text mining, business analytics and predictive analysis. Users are less likely to write code in this tool.
- Project R
In recent years, the popularity of R language has increased extensively. It is a free software environment and programming language used for graphics and statistical computing.
If you consider programming in Python, then this tool is totally made for you. It is not only easy to use but also comes withexcellent visual programming and scripting. Besides the main functionalities, it includes add-ons for bioinformatics, text mining, and data fusion.
Konstanz Information Miner provides you a GUI for the entire analysis process. It comprises of all three main ETL components i.e. extraction, transformation, and loading. It combines various machine learning and data mining components through its modular pipelining concept.
- NLTK (Natural Language ToolKit)
As the name suggests, it works with human language data. You can use this tool for sentiment analysis, opinion mining, data scraping, and other various language processing tasks.
Since it is a Python-based tool, you can customize it for small tasks. The best part is that it is a free and community-driven tool.
This machine learning library is a project of Apache Software Foundation. You can use it for mining comparatively large datasets. With the support of clustering,recommendation mining, frequent itemset mining, and clustering, it can produce implementations of scalable or distributed machine learning algorithms for free.
This software provides you with a GUI for data mining which uses R programming language. The impressive factor is that it captures all the interactions with the GUI as R scripts that can be executed later using R independently.
Shogun is a free toolbox written in C++. In fact, you can use it via a unified interface with C++, Python, R, Java, Ruby, Octave, C#,etc. It mainly focuses on bioinformatics and large-scale kernel methods such as support vector machines (SVM) for classification and regression problems.