Workshop Announcement: Effective Feature Engineering Workshop

Join our workshop on Effective and useful feature engineering, which is a part of our workshops for Ukraine series! 

Here’s some more info: 

Title: Effective and useful feature engineering

Date: Thursday, October 2nd, 18:00 – 20:00 CEST (Rome, Berlin, Paris timezone)

Speaker: Emil Hvitfeldt is a software engineer at Posit and part of the tidymodels team’s effort to improve R’s modeling capabilities. He maintains several packages within the realms of modeling, text analysis, and color palettes. Trying to make slidecrafting a well respecting verb. He co-authored the book Supervised Machine Learning for Text Analysis in R with Julia Silge. Working on book Feature Engineering A-Z.

Description: Feature engineering is one of the fundamental part of the modeling pipeline that is often overlooked to great dismay. This workshop will go over a number of practical examples, going over the most common problems that feature engineering solves. Including dealing with numeric predictors, time predictors, and categorical predictors. A practical component is included, which will use the R package {recipes} and its extension packages.

Minimal registration fee: 20 euro (or 20 USD or 800 UAH)

Please note that the registration confirmation is sent 1 day before the workshop to all registered participants rather than immediately after registration

How can I register?

• Go to https://bit.ly/3wvwMA6 or https://bit.ly/4aD5LMC  or  https://bit.ly/3PFxtNA and donate at least 20 euro. Feel free to donate more if you can, all proceeds go directly to support Ukraine.

• Save your donation receipt (after the donation is processed, there is an option to enter your email address on the website to which the donation receipt is sent)

• Fill in the registration form, attaching a screenshot of a donation receipt (please attach the screenshot of the donation receipt that was emailed to you rather than the page you see after donation).

If you are not personally interested in attending, you can also contribute by sponsoring a participation of a student, who will then be able to participate for free. If you choose to sponsor a student, all proceeds will also go directly to organisations working in Ukraine. You can either sponsor a particular student or you can leave it up to us so that we can allocate the sponsored place to students who have signed up for the waiting list.

How can I sponsor a student?

• Go to https://bit.ly/3wvwMA6 or https://bit.ly/4aD5LMC  or https://bit.ly/3PFxtNA and donate at least 20 euro (or 17 GBP or 20 USD or 800 UAH). Feel free to donate more if you can, all proceeds go to support Ukraine!

• Save your donation receipt (after the donation is processed, there is an option to enter your email address on the website to which the donation receipt is sent)

• Fill in the sponsorship form, attaching the screenshot of the donation receipt (please attach the screenshot of the donation receipt that was emailed to you rather than the page you see after the donation). You can indicate whether you want to sponsor a particular student or we can allocate this spot ourselves to the students from the waiting list. You can also indicate whether you prefer us to prioritize students from developing countries when assigning place(s) that you sponsored.

If you are a university student and cannot afford the registration fee, you can also sign up for the waiting list here. (Note that you are not guaranteed to participate by signing up for the waiting list).

You can also find more information about this workshop series,  a schedule of our future workshops as well as a list of our past workshops which you can get the recordings & materials here.

Looking forward to seeing you during the workshop!

Continue reading: Effective and useful feature engineering workshop

Long-term Implications and Future Developments of the ‘Effective and Useful Feature Engineering’ Workshop Series

The “Effective and Useful Feature Engineering” workshop organized as part of the ‘workshops for Ukraine’ series offers a salient insight into the growing importance of machine learning, data analysis, and related technologies. The key takeaways and potentials for future development present a compelling narrative for the wider tech and academic community.

Feature Engineering’s Growing Significance

The workshop underscores the importance of feature engineering – a fundamental, yet often overlooked aspect of the machine learning modeling pipeline. With the growing ubiquity of machine learning applications across industries and research disciplines, mastering feature engineering can be a game-changer. As noted in the workshop, proficient skill in handling numeric predictors, time predictors and categorical predictors is crucial for creating advanced machine learning models that are robust, accurate, and efficient.

The featured speaker, Emil Hvitfeldt, supports R’s development, particularly in improving its modeling capabilities. His co-authorship of “Supervised Machine Learning for Text Analysis in R” and his work on the “Feature Engineering A-Z” book, further emphasize his expertise and the value participants are likely to gain.

Future Developments

Encouragingly, this workshop could be the harbinger for more such initiatives that bring feature engineering and related machine learning concepts to the forefront. Given the growing prominence of machine learning and data analytics in various aspects of our digital life, strengthening fundamental skills such as feature engineering will likely become increasingly important.

Actionable Advice

For Participants and Interested Individuals

This workshop presents an excellent opportunity to learn from a text analysis and feature engineering expert, helping you to strengthen your skills in data modeling. Additionally, investing in such workshops would be beneficial in building a strong foundation for future learning or career advancements within the field of machine learning and data science.

For Event Organizers and Educational Institutes

Following the model of this workshop series for Ukraine, future events could focus on advanced and specialized topics in machine learning and data science. Moreover, adopting a philanthropic approach, such as minimal registration fees that further charitable causes, could also be an effective strategy for widening access to these learning opportunities.

For Students

Students’ participation in such workshops can equip them with the skills and knowledge that are currently in high demand in the job market. For those who cannot afford the registration fee, initiatives like assembling waiting lists or enabling workshop sponsorships from other attendees present alternative avenues of access.

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