Is data science a mysterious process in which raw data is turned into gold in a way that cannot be understood? As a data scientist, I am often confronted with this myth. But is it actually true? In “Torch”, our new data science series, I will show you a typical data science procedure, called CRISP-ML, so you can make up your own mind.
How CRISP-ML works and how you can use it for your own data science project.
What business questions you have to ask before even starting the project.
Why iteration is at the core of data science.
Want to see this on a real-life example? In my takeaway, I show you how we apply CRISP-ML for customers and how you too can make data science projects fly.
Hi, I'm Lev, and I've been a data scientist at Trivadis – Part of Accenture for over seven years. When I'm not shooting videos, I support a wide variety of companies in developing and implementing data-driven solutions. I also teach data science and data analytics at the Haute École Arc in Neuchâtel. I am known for always questioning things and uncompromisingly looking for the best approach in a project. And when I'm not working on algorithms and statistics? Then I like to kill monsters and save the world on my video game console. PS: Did you enjoy my “Torch” episode? Then let’s get in touch – I would love to pass the torch and discuss the world of data science further!
What I share with you
To obtain more accurate forecasts of product demand, we used CRISP-ML, a standard procedure for data science projects, at a consumer goods company. What challenges did we encounter and how did we solve them? In this takeaway, you'll get concrete tips on how to make your own data science project a success.
