The Conference for Machine Learning Innovation

Vladimir Rybakov

Vladimir Rybakov
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Register until October 21:
✓ 50% off on all prices
✓ 10% team discount
Register Now
Join the ML Revolution!
Register until September 23:
✓ PS Classic or C64 Mini for free
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10 % Team Discount
Register Now
Join the ML Revolution!
Register until September 23:
✓ PS Classic or C64 Mini for free
✓ Save up to €310
10 % Team Discount
Register Now
Join the ML Revolution!
Register until the conference starts:
✓ 2-in-1 conference special
✓ 10 % Team Discount
Register Now
Join the ML Revolution!
Register until the conference starts:
✓ 2-in-1 conference special
✓ 10 % Team Discount
Register Now

Vladimir Rybakov

WaveAccess

Vladimir holds a master’s degree in engineering. He became interested in machine learning and data science since the first years of studying. During that time, he published several publications, participated in two grants, and wrote both his baccalaureate’s and master’s papers in the field of ML. Since 2015, Vladimir manages the ML R&D team in WaveAccess.

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

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All talks by Vladimir Rybakov

Singapore 2021 Singapore 2021 -

Essential Workshop to Exploratory Data Analysis and Feature Engineering



Singapore 2021 Singapore 2021 -

Real Machine Learning challenges that you’ve never faced at Kaggle




All talks by Vladimir Rybakov from other editions

Munich 2020 Munich 2020 -

Satellite imagery analysis: Machine Learning to prevent environmental crisis



Berlin 2019 Berlin 2019 -

Case Study: Making the Most out of a Doomed Project



Munich 2019 Munich 2019 -

Does Deep Learning make Feature Engineering obsolete?



Berlin 2018 Berlin 2018 -

The challenge of putting ML into practice



All talks by Vladimir Rybakov

No current talks available.

All talks by Vladimir Rybakov from other editions

Singapore 2021 Singapore 2021 -

Essential Workshop to Exploratory Data Analysis and Feature Engineering



Munich 2020 Munich 2020 -

Satellite imagery analysis: Machine Learning to prevent environmental crisis



Singapore 2020 Singapore 2020 Singapore 2021 Singapore 2021 -

Real Machine Learning challenges that you’ve never faced at Kaggle



Berlin 2019 Berlin 2019 -

Case Study: Making the Most out of a Doomed Project



Munich 2019 Munich 2019 -

Does Deep Learning make Feature Engineering obsolete?



Berlin 2018 Berlin 2018 -

The challenge of putting ML into practice



All talks by Vladimir Rybakov

No current talks available.

All talks by Vladimir Rybakov from other editions

Singapore 2021 Singapore 2021 -

Essential Workshop to Exploratory Data Analysis and Feature Engineering



Munich 2020 Munich 2020 -

Satellite imagery analysis: Machine Learning to prevent environmental crisis



Singapore 2020 Singapore 2020 Singapore 2021 Singapore 2021 -

Real Machine Learning challenges that you’ve never faced at Kaggle



Berlin 2019 Berlin 2019 -

Case Study: Making the Most out of a Doomed Project



Munich 2019 Munich 2019 -

Does Deep Learning make Feature Engineering obsolete?



Berlin 2018 Berlin 2018 -

The challenge of putting ML into practice



All talks by Vladimir Rybakov

Singapore 2021 Singapore 2021 -

Essential Workshop to Exploratory Data Analysis and Feature Engineering



Singapore 2021 Singapore 2021 -

Real Machine Learning challenges that you’ve never faced at Kaggle




All talks by Vladimir Rybakov from other editions

Munich 2020 Munich 2020 -

Satellite imagery analysis: Machine Learning to prevent environmental crisis



Berlin 2019 Berlin 2019 -

Case Study: Making the Most out of a Doomed Project



Munich 2019 Munich 2019 -

Does Deep Learning make Feature Engineering obsolete?



Berlin 2018 Berlin 2018 -

The challenge of putting ML into practice



Behind the Tracks