Most hardest part of any Data Science Project is Data Collection and Data Cleaning. – Mayur Domadiya

Interview with Mayur Domadiya

Mayur Domadiya

Data Scientist
Surat, Gujarat, India

Q1. Please share your educational and professional journey?

I completed my B.Tech in computer engineering from Surat. After completing my graduation I joined as machine learning engineer at a company in Navsari and joined in product base company as data scientist. I have gained an experience of one plus year in this product based company.

Q2. What did attract you towards Data Science Domain?

During last year project in collage we successfully developed machine learning and computer vision project during this we got to learn many concepts in ML which attracted me to work in data science domain.

Q3. What is the best procedure to solve any Data Science Problem?

My point of view is to first identify the problem and get the requirement of problem, then you move to data collection part after completing it you move to data analysis. After all these steps follow machine learning model pipeline.

Q4. Which one is the hardest working part of any Data Science Project?

Most hardest part of any Data Science Project is Data Collection and Data Cleaning. Only this step in data science take long time if you don’t have proper data then your model can not learn patterns so always focus this step.

Q5. Which Machine Learning Model have you used maximum in your career?

In my experience I have spent most of time on recommendation system. So most of time, I am using K Nearest Neighbour algorithm, matrix factorization and SVM algorithm. Few a times I have also used VGG model for transfer learning.

Mayur Domadiya

Q6. Which are the best Online Courses for Data Scientist?

If you are beginner, you should take Andrew NG Machine Learning and Deep Learning courses and you can find good tutorials on YouTube channel like codebasics, krish Naik and AI Engineering.

Q7. How do you see Deep Learning for any Data Scientist as a career?

Well it forms the baseline for any model training and obtaining patters and information on any large data. And as it is said data is going to be the future, deep learning is going to help a lot in various domains like business decisions, IOT, etc.  

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