Machine Learning R
This Machine Learning with R course dives into the basics of machine learning using an approachable, and well-known, programming language. You’ll learn about Supervised vs Unsupervised Learning, look into how Statistical Modelling relates to Machine Learning, and do a comparison of each.
- Analyze data find relative patterns to predict outcomes
- Analyze continuous data in varying scenarios
- Analyze and find patterns in data by applying various techniques
- Expert in Confirmatory Data analysis
- Analyze continuous data by applying various testing, regression and correlation scenarios
- Implement key components specific to text mining and analytics aided by the real world datasets and text mining
- Demonstrate expert knowledge in predicting outcomes
- Who are familiar with R and looking for some advanced topics.
- No prior programming knowledge is needed.
- Genuine Interest in statistical programming
- Computer ready to run R and RStudi
- Basic understanding of statistics and data structure
- NO prior knowledge in programming is required!
- Introduction to Analytics
- Data Description
- Basic R
- Data Preprocessing
- Linear Regression Model
- Logistic Regression
- K Nearest Neighbours Algorithm for Classification
- Naïve Bayes Algorithm
- Decision Tree
- Random Forests
- Support Vector Machines with case study
- Unsupervised Learning – Clustering
- Association Rule Mining
- Time Series
- Discussion on Application of Algorithms