19 Data Science Tools for people who aren’t so good at Programming

This list of Data Science tools for people who aren’t so good at Programming was compiled by Aarshay Jain, from Analytics Vidhya.

Programming is an integral part of data science. Among other things, it is considered that a mind which understands programming logic, loops, and functions has higher chances of becoming a successful data scientist. So, what about people who never studied programming subject in their school or college ?

The list of tools:

1. RapidMiner (RM)

RM covers the entire life-cycle of prediction modeling, starting from data preparation to model building and finally validation and deployment.

2. DataRobot (DR)

DataRobot (DR) is a highly automated machine-learning platform built by all time best Kagglers including Jeremy Achin, Thoman DeGodoy and Owen Zhang.

3. BigML

BigML is another platform with ~Mn USD in funding. It provides a good GUI which takes the user through 6 steps.

4. Google Cloud Prediction API

The Google Cloud Prediction API offers RESTful APIs for building machine learning models for android applications.

5. Paxata

Paxata is one of the few organizations which focus on data cleaning and preparation, NOT the machine learning or statistical modeling part.

6. Trifacta

Trifacta is another startup focused on data preparation.

It has 2 products offering:

Wrangler – a free stand-alone software
Wrangler Enterprise – licensed professional version

7. Narrative Science

Narrative Science is based on a unique idea in the sense that it generates automated reports using data.

8. MLBase

MLBase is an open-source project developed by AMP (Algorithms Machines People) Lab at University of California, Berkeley.

9. WEKA

Weka is a data mining software written in Java, developed at the Machine Learning Group at University of Waikato, New Zealand.

10. Automatic Statistician

Automatic Statistician is not a product per se but a research organization which is creating a data exploration and analysis tool.

Find more tools in the full article: If you want to learn more about the 19 tools quoted above click here. For other articles about Data Science tools click here.

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Comment by Prasanth on February 19, 2019 at 9:03am: Any open-source tools ? All are Licenced ?

Comment by Dr S Kotrappa on April 18, 2017 at 11:12pm: Really wonderful article thank you !

Comment by Paul McLeod on March 15, 2017 at 3:41pm: What a great topic. DR and BigML in particular are definitely strong standout options.

However, it seems to me that the IBM SPSS Modeler would be a THE goto for most general purpose prediction. It is very comprehensive (and it can also be scripted, integrated with R and can be used as a framework for deployment). No lightweight, not at all.. but is entirely graphical. The focus is on the modeling - so a good choice especially for technical/statsy people who choose not to code..

Of course, SPSS is not freeware, ..not sure that's a criteria.

PS. IBM also have Data Science Experience, which is a wonderful IDE for coding R, Python, Scala.. but of course.. coding is another story again.

Thanks again for the list!

Cheers,

Paul