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June 2019

Advanced Machine Learning Masterclass: Sydney, 5–6 June 2019

June 5 @ 9:30 am - June 6 @ 5:00 pm
City Training Rooms, Sydney, Suite 401/60 York Street
Sydney, NSW 2000 Australia
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This course is for experienced machine-learning practitioners who want to take their skills to the next level by using R to hone their abilities as predictive modellers. Trainees will learn essential techniques for real machine-learning model development, helping them to build more accurate models. In the masterclass, participants will work to deploy, test, and improve their models. Topics covered will include data exploration, data preparation, feature engineering, and prediction, using advanced modelling techniques including glmnet, xgboost, and random forests. Participants…

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Advanced masterclass 2 – Random forests: Canberra, 20–21 June 2019

June 20 @ 9:30 am - June 21 @ 5:00 pm
Atlas Computer Training, Canberra, Level 1, 33–35 Ainslie Place
Canberra, ACT 2601 Australia
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This class will explore the many unique applications and extensions of the randomForest package, many of which are implemented in R. Access to these methods allows the user to easily solve problems not susceptible to other methods, including deep learning. Topics will include: A brief overview of the random forest algorithm. Out-of-sample estimates on training data, and applications in fraud, risk and outlier detection—random forests can make confident predictions on training data, unlike most other methods. Single-model quantile regression—estimating a…

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July 2019

Advanced Machine Learning Masterclass: Canberra, 10-11 July 2019

July 10 @ 9:30 am - July 11 @ 5:00 pm
Atlas Computer Training, Canberra, Level 1, 33–35 Ainslie Place
Canberra, ACT 2601 Australia
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This course is for experienced machine-learning practitioners who want to take their skills to the next level by using R to hone their abilities as predictive modellers. Trainees will learn essential techniques for real machine-learning model development, helping them to build more accurate models. In the masterclass, participants will work to deploy, test, and improve their models. Topics covered will include data exploration, data preparation, feature engineering, and prediction, using advanced modelling techniques including glmnet, xgboost, and random forests. Participants…

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