Machine Learning with R

Why learn Data Analysis and Data Science?

According to SAS, the five reasons are

1. Gain problem solving skills

The ability to think analytically and approach problems in the right way is a skill that is very useful in the professional world and everyday life.

2. High demand

Data Analysts and Data Scientists are valuable. With a looming skill shortage as more and more businesses and sectors work on data, the value is going to increase.

3. Analytics is everywhere

Data is everywhere. All company has data and need to get insights from the data. Many organizations want to capitalize on data to improve their processes. It's a hugely exciting time to start a career in analytics.

4. It's only becoming more important

With the abundance of data available for all of us today, the opportunity to find and get insights from data for companies to make decisions has never been greater. The value of data analysts will go up, creating even better job opportunities.

5. A range of related skills

The great thing about being an analyst is that the field encompasses many fields such as computer science, business, and maths.  Data analysts and Data Scientists also need to know how to communicate complex information to those without expertise.

The Internet of Things is Data Science + Engineering. By learning data science, you can also go into the Internet of Things and Smart Cities.

This is the bite-size course to learn R Programming for Machine Learning and Statistical Learning. In CRISP-DM data mining process, machine learning is at the modeling and evaluation stage. 

You will need to know some R programming, and you can learn R programming from my "Create Your Calculator: Learn R Programming Basics Fast" course.  You will learn R Programming for machine learning and you will be able to train your own prediction models with Naive Bayes, decision trees, knn, neural network, and linear regression, and evaluate your models very soon after learning the course.

You can take the course as follows, and you can take an exam at EMHAcademy to get SVBook Certified Data Miner using R certificate : 

- Create Your Calculator: Learn R Programming Basics Fast (R Basics)

- Applied Statistics using R with Data Processing (Data Understanding and Data Preparation)

- Advanced Data Visualizations using R with Data Processing (Data Understanding and Data Preparation, in the future)

- Machine Learning with R (Modeling and Evaluation)

Content

1. Getting Started

2. Getting Started 2

3. Getting Started 3

4. Data Mining Process

5. Download Data set

6. Read Data set

7. Some Explanations

8. Simple Linear Regression

9. Build Linear Regression Models

10. Predict Linear Regression Models

11. KMeans Clustering

12. KMeans Clustering in R

13. Agglomeration Clustering

14. Agglomeration Clustering in R

15. Decision Tree ID3 Algorithm

16. Decision Tree in R: Split train and test set

17. Decision Tree in R: Train Decision Tree

18. Decision Tree in R: Predict Decision Tree

19. KNN Classification

20. Train KNN in R

21. Predict KNN in R

22. Naive Bayes Classification

23. Naive Bayes in R

24. Neural Network Classification

25. Neural Network in R

26. What Algorithm to Use?

27. Model Evaluation

28. Model Evaluation using R for Classification

29. Model Evaluation using R for Regression