# Machine Learning and Statistical Modeling with R Examples

Udemy free download **Machine Learning and Statistical Modeling with R Examples**, with this course you can Learn how to use machine learning algorithms and statistical modeling for clustering, decision trees, etc by using R This course By **R-Tutorials Training** "Data Science Education".

24 lectures and 1 generic quizzes On-demand course with full lifetime Access multiple devices. **DOWNLOAD YOURS NOW.**

One way to know the usability of the course to know how many students took the course. Because if large number of people are taking this course, it means it has some value. So far, the total number of enrolments have crossed **2283**.

But enrolment alone is not a good yardstick to measure the value of any course. But positive reviews are!

This Udemy free download course was created in created and has an average **4.4** star rating out of 5. The total reviews for this course are **174** which is a number of reviews and ratings.

## What Will You Learn From This Course?

- understand the most common principles of machine learning and statistical modeling
- perform machine learning tasks in R
- understand which machine learning tool is suitable for a given problem
- know what machine learning can do
- implement machine learning and statistical modeling in your work

## What this instructor say's about His tutorial ?

**See things in your data that no one else can see – and make the right decisions!**

Due to modern technology and the internet, the amount of available data grows substantially from day to day. Successful companies know that. And they also know that seeing the patterns in the data gives them an edge on increasingly competitive markets. Proper understanding and training in **Machine Learning** and **Statistical Modeling** will give you the power to identify those patterns. This can make you an invaluable asset for your company/institution and can* boost your career*!

*Marketing companies* use Machine Learning to identify potential customers and how to best present products.

*Scientists* use Machine Learning to capture new insights in nearly any given field ranging from psychology to physics and computer sciences.

*IT companies* use Machine Learning to create new search tools or cutting edge mobile apps.

*Insurance companies, banks and investment funds* use Machine Learning to make the right financial decisions or even use it for algorithmic trading.

*Consulting companies* use Machine Learning to help their customers on decision making.

Artificial intelligence would not be possible without those modeling tools.

Basically we already live in a world that is heavily influenced by Machine Learning algorithms.

1. But what exactly is Machine Learning?

Machine learning is a collection of modern statistical methods for various applications. Those methods have one thing in common: they try to create a model based on underlying (training) data to predict outcomes on new data you feed into the model. A test dataset is used to see how accurate the model works. Basically Machine learning is the same as **Statistical Modeling**.

2. Is it hard to understand and learn those methods?

Unfortunately the learning materials about Machine Learning tend to be quite technical and need tons of prior knowledge to be understood.

With this course it is my main goal to make understanding those tools as** intuitive** and **simple** as possible.

While you need some knowledge in statistics and statistical programming, the course is meant for people without a major in a quantitative field like math or statistics. Basically anybody dealing with data on a regular basis can benefit from this course.

3. How is the course structured?

For a better learning success, each section has a* theory part*, a* practice part* where I will show you an example in R and at last every section is enforced with ** exercises.** You can download the

**code pdf**of every section to try the presented code on your own.

4. So how do I prepare best to benefit from that course?

It depends on your prior knowledge. But as a rule of thumb you should know how to handle standard tasks in R (courses *R Basics* and *R Level 1*). You should also know the basics of modeling and statistics and how to implement that in R (*Statistics in R* course).

For special offers and combinations just check out the **r-tutorials webpage** which you can find below the instructor profile.

What R you waiting for?

Martin

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Here we are presenting one of the courses on Udemy for free. If you want to learn **Development** this course will help you in **Learn how to use machine learning algorithms and statistical modeling for clustering, decision trees, etc by using R** and to increase your knowledge about it. Below are the complete details of this course visit this link and start **Udemy free download now.**

**Udemy Free Download Machine Learning and Statistical Modeling with R Examples**

**Rating:**

4.4