A Thank You note to Towards Data Science

Data Science is not easy, but thanks to many publications like Towards Data Science is easier now to understand hard concepts in an easy way. This article is my way of saying thanks for their contribution to the field and society.

Data Science, a new kind of Science (or is it?)

Data Science is an interdisciplinary field, a new kind of science very related to business. As I stated before, I think Data Science enable us to create intelligence through AI.

And yes, I stated is a “new” kind of science because I think the name of this publication is what we are doing, we are walking on a path Towards making Data Science a Science. I think it could be very useful that Data Science is a Science because if that’s the case, every project in Data Science should be at least:

Reproducible: Necessary for making easy to test other’s work and analysis.

More on this here:

Data Science's Reproducibility Crisis

Toward Reproducibility: Balancing Privacy and Publication

Falible: Data Science and Science are not looking for the truth, they look for
knowledge, so every project can be substituted or improved in the future, no
solution is the ultimate solution. You can read about that here and here.

Collaborative: The data scientist doesn’t exists alone, she/he needs a team, this team will make things possible for creating intelligence and solutions. Collaboration is a big part of science, and data science should not be an exception.

What is the most effective way to structure a data science team?

Building a Data Science Team | Coursera

Creative: Most of what data scientists do is new research, new approaches or takes on different solutions, so their environment should be very creative and easy to work. Creativity is crucial in science, is the only way we can find solutions to hard and complex problems.

Creativity is Crucial in Data Science

What is the role of creativity in data science?

Compliant to regulations: Right now there are a lot of regulations on Science, not that much on Data Science, but there will be more in the future. Is important that the projects we are building can be aware of these different types of regulations so we can create a clean and acceptable solution to the problems.

Will GDPR Make Machine Learning Illegal?

'Your data privacy was updated' - Thanks for ignoring it yet again!

Why is Data Science so hard and so simple at the same time?

So going back to the point on how Data Science enable us to create intelligence through AI, I would like to state that Data Science is hard and simple at the same time.

I think Data Science is hard because of all the things you have to know and understand to consider yourself a Data Scientist: read papers, books, know how to program, understand businesses and how to apply your knowledge to solve their problems, etc.

And at the same time I think is easy, or somewhat easy, because we have a vibrant community of people trying to help each other, sharing thoughts and knowledge, sharing experiences and feelings, the process they followed to become data scientists, how well or bad they are doing in their jobs, and great blogs, publications, webinars, videos, information, infographics and much more tools that are making the transition to Data Science way easier than it could be.

In this is why I want to thank the editors TDS Team, Ludovic Benistant, writers and people contributing to this amazing publication. I also want to thank Medium and the Medium Staff for creating this great platform for us to share ideas, knowledge and experiences.

I would like to end with a thought I had several months ago and was reminded recently for me by Christian Willig, and for me Towards Data Science has been one of the main ways for me to start accomplishing that:

You can make an impact, you can change the world doing what you love.

Many times we’ve heard that it’s impossible to change how things work, or how the world works. That nothing you can do would change it, you are just an ant in this huge planet.

This is not true. You can change the world. You can make things better, and you have to start by changing the way you see things. I work hard for me, my family and loved ones, and if someone is living better, I’m already making a change.

Then you think bigger, how can I make this place a better place for me and other? How can I improve the way a certain process is done?

Find something that you love doing, for me was Science (physics) and Data Science. I love this field. And I hope that sharing what I do, the open source projects I contribute, my work at the companies that hired me, and the things I’ll be doing in the near future will make this world a better place to live.

Believe in what you do, do it with passion, listen to others, work hard, have time for your family, have fun, and believe you will change the world.

Here are my publications on TDS, I hope you liked them, and I expect to write more and more of them in the near future:

How to get a job as a Data Scientist?

My journey into Deep Learning

Skejul meetings with Deep Learning

The two sides of Getting a Job as a Data Scientist

A “weird” introduction to Deep Learning

Creating Intelligence with Data Science

Deep Learning With Apache Spark — Part 1

How to use PySpark on your computer

Going Beyond with Agile Data Science

Detecting Breast Cancer with Deep Learning

Deep Learning With Apache Spark — Part 2

DIY Deep Learning Projects

Thanks for everything :)

Thanks for reading. I hope you found something interesting here :)

If you have questions just add me on twitter:

Favio Vázquez (@FavioVaz) | Twitter

and LinkedIn:

Favio Vázquez — Principal Data Scientist — OXXO | LinkedIn

See you there :)