🚀 @SBERLOGABIO webinar data science, bioinformatics:
👨🔬 John Mitchell "Kaggle Competition Review: Novozymes Enzyme Stability Prediction"
⌚️ Friday 18 August, 19.00 (Moscow time)
Link to Announcement on Kaggle.
Add to Google Calendar
Kaggle's Novozymes Enzyme Stability Prediction was a challenging competition that rewarded expertise in bioinformatics as much as in Machine Learning. Two issues that made the competition particularly difficult were that the training data was rather different from the test data, and that there was no obvious or easy local validation protocol available. A wide variety of features and models proved valuable, while ensembling was generally considered essential. The nature of the competition lent itself to overfitting, and it was unsurprising that there was a large shake-up between Public LB and Private LB ranks. I discuss the experience gained from this competition and consider how the lessons learned might be applicable to other bioinformatic competitions.
About the reporter:
John Mitchell is expert both in bioinformatics and machine learning, and also experienced Kaggler and one of the top participants of CAFA5 , will share his experience on the past Kaggle competition "Novoenzymes" which in certain respects similar to CAFA5 challenge.
Zoom link will be available in https://t.me/sberlogabig shortly before start of the talk.
📹 Video record: https://youtu.be/M8tqVF4Gyi0
📖 Presentation: https://t.me/sberlogabio/59283
👨🔬 John Mitchell "Kaggle Competition Review: Novozymes Enzyme Stability Prediction"
⌚️ Friday 18 August, 19.00 (Moscow time)
Link to Announcement on Kaggle.
Add to Google Calendar
Kaggle's Novozymes Enzyme Stability Prediction was a challenging competition that rewarded expertise in bioinformatics as much as in Machine Learning. Two issues that made the competition particularly difficult were that the training data was rather different from the test data, and that there was no obvious or easy local validation protocol available. A wide variety of features and models proved valuable, while ensembling was generally considered essential. The nature of the competition lent itself to overfitting, and it was unsurprising that there was a large shake-up between Public LB and Private LB ranks. I discuss the experience gained from this competition and consider how the lessons learned might be applicable to other bioinformatic competitions.
About the reporter:
John Mitchell is expert both in bioinformatics and machine learning, and also experienced Kaggler and one of the top participants of CAFA5 , will share his experience on the past Kaggle competition "Novoenzymes" which in certain respects similar to CAFA5 challenge.
Zoom link will be available in https://t.me/sberlogabig shortly before start of the talk.
📹 Video record: https://youtu.be/M8tqVF4Gyi0
📖 Presentation: https://t.me/sberlogabio/59283