Did you feel like a lost bird when you started learning Machine learning? Do you learn coding on a language first? Or you focus on understanding the math / logic behind machine learning algorithms? Or you look for ways to handle the large datasets efficiently? Statistics?
If you have come from a non-quant background, there is a good chance that you would feel like this:
Worry not! The data science community has found ways to induct you in less harsher ways in its ecosystem. You will still need to do the hard work, but you can focus on learning one thing at a time.
One of the tools, which helps you learn machine learning through a Graphical User Interface (GUI) is Weka. Weka was a project at University of Waikato and can be a good stepping stone for beginners. Once you are more comfortable with machine learning and various algorithms, you can always switch back to a more evolved language like R or Python.
So, here is a learning path on Weka, which was designed by Abhinav Unnam, who interned with us last summer. He himself started his machine learning journey through Weka. If you have any question related to starting machine learning journey through Weka, please feel free to ask them here or on our discussion portal
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Kunal is a post graduate from IIT Bombay in Aerospace Engineering. He has spent more than 10 years in field of Data Science. His work experience ranges from mature markets like UK to a developing market like India. During this period he has lead teams of various sizes and has worked on various tools like SAS, SPSS, Qlikview, R, Python and Matlab.
