Many terms in data analytics are still not clear. Very First, it needs to understand there is no clear single definition of data science and data mining. Most people make a definition or build, then other people change the term or phrases to redescribe it.
Data science is a broader term covering AI, ML, NLP, a type of model or principle, and data set preprocessing. Many people bother about it saying this is nonsense, as every domain of data science describes the different purposes that combine together for a solution. So, data science is not pure data mining.
“Data Mining is process of collecting past data for finding and searching patterns within it. “
Combination of Artificial Intelligence, Machine Learning, Data mining, Big Data, Data Visualization, and data analysis make a class which is called Data Science.
Data science works with the collaboration of some programming languages (Python), mathematics, and statistics. Therefore, data mining is a part of data science, preprocessing is part of it. Preprocessing is a technique to clean the data for learning features.
How to Learn Data Mining from Scratch?
Do you have basic knowledge of programming, and linear algebra? If yes then it is a good time to take a step in. Practice, practice, and practice will lead you to become a data mining engineer.
Have A Study Plan
Spare time for reading books on data mining and learning the different methods and how they work. The best time for study is in the morning and making points. Collect new models, and know their working of them. For example, data cleaning is deleting unnecessary data from the columns and rows.
Dataset Insights
Download datasets from different websites and see how the code is working in them. To learn the work you must have the skill of python libraries pandas, NumPy, scikit, and matplotible. Learning will begin when you work with different datasets and see more insights. Expect this to join an online community like Kaggle for practice.
Work On Projects
Projects are the best source for learning what is going on inside them. It depends on how much effort you put into it. Remember, focused efforts are a very important step that will teach you consistency and find out patterns from it. Spending almost 6 months on different projects with concentrated efforts will get you into the data mining world.
- Step by Step Guide to Machine Learning
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