Explore Data Analytics with Zero Coding Skills For Free

Explore Data Analytics with Zero Coding Skills For Free

All you need is to explore these open source tools online. Have you been hearing the new industry buzzword — Data Analytics(it was AI-ML earlier) a lot lately? Does it sound complicated and yet simple enough? Understand the logic behind models but don't know how to code? Apprehensive of spending too much time learning to code before jumping on the bandwagon?

Have you been hearing the new industry buzzword — Data Analytics(it was AI-ML earlier) a lot lately? Does it sound complicated and yet simple enough? Understand the logic behind models but don't know how to code? Apprehensive of spending too much time learning to code before jumping on the bandwagon?

Worry not, there are some awesome tools available for free for non-coders that can help develop complicated models in no time. These tools are completely free for personal use, extremely easy and intuitive and can help one practice without the hassle of learning how to code.

I am an amateurish coder but a big machine learning enthusiast. I can code but I avoid it as much as I can _(Thank God for that Recording Macro option in Excel), _till the point I cannot avoid it.

I was working on developing a model for forecasting traffic on a road and had to try a lot of things when I started looking for non-coder resources and found these gems. I am discussing the best three I found. Again, these are open source for individual users but have priced versions for commercial uses.

What These Tools Cannot Do

Please be aware, although these tools remove the need for coding, your understanding of models, basics of data preparation, and statistics should be above the bare minimum. The reason is that when you code, you exactly know what is being done and how, while in most of these tools, default parameters are preloaded, and sometimes the code is not visible to the user. Thus it is easy for model errors to go unnoticed in case the user does not do a thorough QA.

In addition to this, these tools will not tell you which data cleaning technique to use, which model to build, or which statistic to compare instead, the tools will let you do all the above tasks easily and give you more time to think and analyze data.

Now that you have read all the warnings let us directly dive in.

1. Knime Analytics

This is by far, the best tool in the open source domain.

Knime is a very intuitive platform that helps create models using drag and drop nodes in a workflow kind of environment. It is built on python, has widgets for data input, data cleaning, modeling (regression, clustering, classification, Neural Networks, etc), statistics, and majorly used representations.

machine-learning no-code data-science data-analytics open-source

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