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February 2019

Advanced Machine Learning Masterclass: Melbourne, 19–20 February 2018

19 February 2019 @ 9:30 am - 20 February 2019 @ 5:00 pm
Saxons Training Facilities, Melbourne, Saxons Training Facilities, Level 8, 500 Collins Street
Melbourne, Victoria 3000 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 Machine Learning Masterclass: Brisbane, 27–28 February 2019

27 February 2019 @ 9:30 am - 28 February 2019 @ 5:00 pm
Saxons Training Facilities, Brisbane, Level 11, 300 Adelaide Street
Brisbane, QLD 4000 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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March 2019

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

5 March 2019 @ 9:30 am - 6 March 2019 @ 5:00 pm
BCA, Sydney, BCA, Level 1, 65 York Street
Sydney, New South Wales 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: Sydney, 26–27 March 2019

26 March 2019 @ 9:30 am - 27 March 2019 @ 5:00 pm
BCA, Sydney, BCA, Level 1, 65 York Street
Sydney, New South Wales 2000 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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Fraud and anomaly detection: Sydney, 28–29 March 2019

28 March 2019 @ 9:30 am - 29 March 2019 @ 5:00 pm
BCA, Sydney, BCA, Level 1, 65 York Street
Sydney, New South Wales 2000 Australia
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This course presents statistical, computational and machine-learning techniques for predictive detection of fraud and security breaches. These methods are shown in the context of use cases for their application, and include the extraction of business rules and a framework for the interoperation of human, rule-based, predictive and outlier-detection methods. Methods presented include predictive tools that do not rely on explicit fraud labels, as well as a range of outlier-detection techniques including unsupervised learning methods, notably the powerful random-forest algorithm, which…

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