The Conference for Machine Learning Innovation

Feature Engineering and Feature Selection Workshop Part 1

Workshop
Join the ML Revolution!
Register until October 20:
✓ Save up to $233
✓ Team discount
✓ Extra Specials for Freelancers
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Join the ML Revolution!
Register until October 20:
✓ Save up to $233
✓ Team discount
✓ Extra Specials for Freelancers
Register Now
Join the ML Revolution!
Register until November 03:

✓ Save up to €494
✓ 10% Team Discount✓ Special discount for freelancers
Register Now
Join the ML Revolution!
Register until November 03:

✓ Save up to €494
✓ 10% Team Discount✓ Special discount for freelancers
Register Now
Join the ML Revolution!
Until the Conference starts:
✓ Group discount
✓ Special discount for freelancers
Register Now
Join the ML Revolution!
Until the Conference starts:
✓ Group discount
✓ Special discount for freelancers
Register Now
Infos
Thursday, December 1 2022
09:00 - 12:30
Booking note:
Feature Engineering Workshop

Once you know the basics of Machine Learning you might think you just input some data into a model and out comes a great result. As is so often the case, the reality is different. Building a good machine learning model requires you to extract the relevant information from your data, the features.
Once you have all these features, you still need to select which of them are relevant.

In this workshop I will teach you how you go about finding the right set of features to predict the rating of apps in an app store.

Throughout the workshop you will learn the basic concepts of data inspection, data cleaning and feature engineering. Once we have a set of features we will dive into how you can select the optimal set of features to get the best possible result and to minimize overfitting.

Each participant will work individually on his or her own computer in a Jupyter notebook which you will be able to access through a URL provided at the beginning of the workshop. We will use tools like Pandas, sklearn and NumPy.

The goal of this workshop is to teach you the basic concepts of feature engineering and selection. Most of the code will be provided for you so this is not a coding exercise. So if you don’t have a large Python background this won’t be an issue. You will only need to implement the essential parts of the code to really understand the concepts.

Typically this is just around 1-3 lines of code per exercise. At the beginning of each exercise I will introduce you to the task at hand and explain what we are trying to accomplish. During the exercise I will answer all the questions you might have so you don’t need to be stuck on silly coding mistakes. And once the majority of people have finished the exercise I will go over the solutions and I will provide a bit more context to how to apply this in real life tasks.

At the end of the workshop I will provide you with access to the source code of the workshop that contains the solutions. So after the workshop you should be ready to start working with real data for your Machine Learning problems on your own.

Anybody who has a basic understanding of Machine Learning, understands the concepts of fitting a model and knows vaguely what overfitting means should be able to follow the concepts of the workshop. Because you will write some code during the workshop, you’ll need some programming experience. However, the programming language you know probably doesn’t matter. We make use of an iPython/Jupyter Notebook running on a dedicated server, so nothing but a laptop with an internet connection is required to participate.

This Session belongs to the Diese Session gehört zum Programm vom BerlinBerlin program. Take me to the program of . Hier geht es zum Programm von Singapore Singapore .

Take me to the full program of Zum vollständigen Programm von Berlin Berlin .

This Session belongs to the Diese Session gehört zum Programm vom BerlinBerlin program. Take me to the program of . Hier geht es zum Programm von Munich Munich .

This Session Diese Session belongs to the gehört zum Programm von BerlinBerlin program. Take me to the current program of . Hier geht es zum aktuellen Programm von Singapore Singapore , Berlin Berlin or oder Munich Munich .

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