I bet you all heard that more than a half of Kaggle competitions was won using only one algorithm [source].
You probably even gave it a try. It’s so easy to get excited about a dream of getting on top of the leaderboard. Imagine all that fame and fortune, ahh.
Let’s get real. You made it work. The submitted results are good but definitely not the best. Then motivation falls.
Don’t give up! You know that it is possible to get more out of it. Start investigating deeper.
Time (and webpages) passes by. You are overwhelmed and even more confused than in the beginning. There are a lot of detailed, laser-focused guides, but it’s hard to find a more general, easy to follow one.
It starts to resemble Dilberts story:
Additionally more topics relating to each other stars forming:
I have been that way.
I saw a lot of these question asked by other people on different groups or forums (uff, I was not alone). These are common issues. My “Read later” browser bookmark list was getting longer and longer.
And guess what.
I read it all.
Some of them were super boring, some very inspiring. I was determined and time spent cannot get wasted.
A guy named Seneca (Roman philosopher) once said - "While we teach, we learn".
So after spending 100+ hours of exploring all possible catches I present to you….
A 100% free online course that will show you how to use one of the hottest algorithms in 2016. You will learn things like:
Each topic is described from A to Z in a fully reproducible way. It starts with loading data set and takes you through all steps. At the end, you will have a clear vision and be able to use a technique in your cases.
Go through video materials and learn how to harness the algorithm to make it work for your data.
Hi, I'm Norbert. From my early days I used to work with code. I started with Turbo Pascal when I was about 10 years old and didn't stop since then.
Combining software craftsmanship and data engineering skills results in clean and understandable code.
XGBoost has proven its power in many competitions. It might be tempting to jump-in right away, but please take the time and read the recommended prerequisites before doing this.
"Very clear, well-structured and informative, even with a brief read through I can already pick up some helpful knowledge - i.e. how to handle imbalanced dataset"
Project Manager at Airbus
For the things we have to learn before we can do them, we learn by doing them.
“Practical XGBoost in Python” is a part of Parrot Prediction’s ESCO Courses. It's a collection of online data-science courses guided in an innovative way.
The main point is to gain experience from empirical processes. From there we can build the right intuition that can be reused everywhere.
Remember that knowledge without action is useless.