Machine Learning Courses
Understand and apply supervised & unsupervised learning methods, including KNN, Linear & Logistic Regression, Naive Bayes, Tree based methods, SVM, Neural Nets, Deep Learning, Ensembles, Clustering and Association Mining. Learn validation techniques, when to adjust thresholds, feature selection/engineering and how to select best models.
Live, online and instructor led. Dates/times aren’t suitable or for group bookings – please let us know?
Machine Learning Professional
A$1,380 + gst
Course outline:
- Introduction and business scenario
- CRISP-DM
- Visualising data
- k-Nearest Neighbour
- Naïve Bayes
- Linear Regression
- Decision Trees
- Unsupervised Learning:
Clustering
– Hierarchical
– K means
Association Mining
– Market Basket Analysis - Bias vs Variance (Underfitting vs Overfitting)
- Split and cross validation
- Evaluation methods & performance criteria
- Scoring models
Machine Learning Master
A$1,380 + gst
Course outline:
- Introduction and business scenario
- Logistic Regression
- Bagging, Random Forest and GBM
- Ensemble methods
- Support Vector Machines
- Neural Networks
- Deep Learning
- Outlier Detection
- Advanced performance criteria
- ROC plots – Comparison between Models
- Feature Selection: Forward Selection, Backward Elimination
- Feature engineering
- Performance (Cost) Model Optimization
- Model Deployment & monitoring
