HRDF Funded Course - R Machine Learning Training
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Tertiary Infotech
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Details
This R machine learning training course will teach you how to use R to apply powerful machine learning methods and gain an insight into real-world applications. Topics include:
- R machine learning
- Supervised and Unsupervised Learning methods
- Classifications
- Regression
- Clustering
- Neural Networks
HRDF SBL Claimable for Employers Registered with HRDF
For more information about this course please visit :
https://www.tertiarycourses.com.my/r-machine-learning-training.html
Outline
Module 1: Introduction to Machine Learning
- What is Machine Learning (ML)
- R packages for ML
- Installing R ML Packages
Module 2: Datasets
- Iris Dataset
- Mtcars Dataset
- Boston Housing Price Dataset
- Features
- Splitting Datasets for Training/Testing
Module 3: Supervised Learning
- What is Supervised Learning
- Performance Metric
- Decision Tree Classifier
- Random Forest Classifier
- Gaussian Navie Bayes (GNB) Classifier
- Support Vector Machine (SVM) Classifier
- Logistic Regression Classifier
- K-Nearest Neighbors (KNN) Classifier
- Linear Regression: Single and Multivariate,
- Variable Selection
- KNN Regression
Module 4: Unsupervised Learning
- What is Unsupervised Learning
- K-Means Clustering
- Hierarchical Clustering
- Dimensionality Reduction
Module 5: Intro to Neural Network (Optional)
- What is Neural Network
- Multi Layer Perceptron
Speaker/s
Dr Zahra Nazemi has PhD in mathematical statistics from Universiti Putra Malaysia. Her research interests are applied statistics, medical statistics, Bayesian statistics, statistical inference and Software R. She has worked as a lecturer in different
universities more than 4 years. She also consulted and worked on assignments for parametric and non-parametric analysis, univariate and multivariate regression analysis in various areas such as medical, economics and psychology. Her other skills are knowledge
of research methodology, extensive experience with SPSS, AMOS, R and MINITAB and writing and presenting reports. Moreover, she conducted a special training program in mathematical programming including optimization, advanced multivariate data analysis, and
simulation techniques.
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