Writing is a good way to evolve your career. You can go deep in studies you are doing, can generate content to people that may be needing a more friendly view and it is a good way to gain visibility (thinking in future jobs). Once you decided to start a new blog, a doubt pops up: where am I going to post this content?
In April 2018 I started Udacity’s Nanodegree in Machine Learning Engineer. The classes are not cheap and many questions asked me the same thing: does it worth it?
On November I discovered that I was selected for the Outreachy internship program for the batch of December 2018 to March 2019.
When you start entering the data science world, things can become really messy. There are thousands of concepts and meanings, most of them thrown at you at the same time.
AKA magics to plug holes in your dataset
This is the fifth post on my internship on the Outreachy Program with Project Jupyter. The previous posts are available and should be read in order if you want to understand the big picture: Outreachy I Outreachy II Outreachy III Outreachy IV Increasing documentation Native Authenticator was pretty advanced, but we still needed more information available on the documentation. And this got me thinking: what is relevant to make a good documentation?