May 2019
Beginner to intermediate
266 pages
5h 57m
English
Content preview from Hands-On Exploratory Data Analysis with R
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Building a data science portfolio
Now as you get accustomed to a particular language, whether it is R or Python, it is mandatory that you create your own portfolio. Kindly refer to the following steps, which include an approach to creating your own data science portfolio:
- Be visible: Always keep your profile updated with your required skillsets to keep yourself visible in the market.
- Articulate your ability: Try out different features and experiments, and check on the output you get. This will help to articulate your ability and skills for any area of data science.
- Be visual: Always have a look at the trending technologies and the programming languages that are being used. Keep up to date with the algorithms, as algorithms form the base ...
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