Introduction
I’ve spent close to a decade in data science & analytics now. Over this period, I have learnt new ways of working on data sets and creating interesting stories. However, before I could succeed, I failed numerous times. Success doesn’t come easy!
How did I succeed? The answer is simple. Every time I failed, I said to myself, ‘Let’s take one more step’. And I managed to travel a long distance. I learnt statistics, data mining, SAS, R, Python, Machine Learning on the way.
I confess that, in last 10 years, the methods of predictive modeling have become faster. Data is becoming larger than ever. We faced constraints when faced with Big Data. But, people came out with several big data technologies.
It’s overwhelming to see how the things have changed. But, there would still be many who are lagging to catch up with success in data science industry.
Hence, I decided to share 20 things which experience has taught me in the last 10 years. Hope you find them useful. The idea is to help people, who don’t have a mentor to provide them this advice all the time. So go ahead and read!
Some Useful Resources
Learn Machine Learning Algorithms
Learn k- fold Cross Validation
Resources on Neural Networks and Deep Learning
Master Structured Thinking Skill
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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.
