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Complete Machine Learning and Deep Learning With H2O in R

H2O:Master Powerful R Package For Machine Learning, Artificial Neural Networks (ANN) and Deep Learning
4.9
4.9/5
(80 reviews)
694 students
Created by

8.8

Classbaze Grade®

7.0

Freshness

9.5

Popularity

9.2

Material

H2O:Master Powerful R Package For Machine Learning
Platform: Udemy
Video: 4h 21m
Language: English
Next start: On Demand

Best Machine Learning classes:

Classbaze Rating

Classbaze Grade®

8.8 / 10

CourseMarks Score® helps students to find the best classes. We aggregate 18 factors, including freshness, student feedback and content diversity.

Freshness

7.0 / 10
This course was last updated on 11/2019.

Course content can become outdated quite quickly. After analysing 71,530 courses, we found that the highest rated courses are updated every year. If a course has not been updated for more than 2 years, you should carefully evaluate the course before enrolling.

Popularity

9.5 / 10
We analyzed factors such as the rating (4.9/5) and the ratio between the number of reviews and the number of students, which is a great signal of student commitment.

New courses are hard to evaluate because there are no or just a few student ratings, but Student Feedback Score helps you find great courses even with fewer reviews.

Material

9.2 / 10
Video Score: 8.2 / 10
The course includes 4h 21m video content. Courses with more videos usually have a higher average rating. We have found that the sweet spot is 16 hours of video, which is long enough to teach a topic comprehensively, but not overwhelming. Courses over 16 hours of video gets the maximum score.
The average video length is 5 hours 48 minutes of 749 Machine Learning courses on Udemy.
Detail Score: 10.0 / 10

The top online course contains a detailed description of the course, what you will learn and also a detailed description about the instructor.

Extra Content Score: 9.5 / 10

Tests, exercises, articles and other resources help students to better understand and deepen their understanding of the topic.

This course contains:

0 article.
1 resources.
0 exercise.
0 test.

In this page

About the course

                     YOUR COMPLETE GUIDE TO H2O: POWERFUL R PACKAGE FOR MACHINE LEARNING, & DEEP LEARNING IN R    
This course covers the main aspects of the H2O package for data science in R. If you take this course, you can do away with taking other courses or buying books on R based data science as you will have the keys to a very powerful R supported data science framework.
 In this age of big data, companies across the globe use R to sift through the avalanche of information at their disposal. By becoming proficient in machine learning, neural networks and deep learning via a powerful framework, H2O in R, you can give your company a competitive edge and boost your career to the next level!
LEARN FROM AN EXPERT DATA SCIENTIST:
My name is Minerva Singh and I am an Oxford University MPhil (Geography and Environment), graduate. I finished a PhD at Cambridge University, UK, where I specialized in data science models.
I have +5 years of experience in analyzing real-life data from different sources using data science-related techniques and producing publications for international peer-reviewed journals.
Over the course of my research, I realized almost all the R data science courses and books out there do not account for the multidimensional nature of the topic.
This course will give you a robust grounding in the main aspects of practical neural networks and deep learning. 
Unlike other R instructors, I dig deep into the data science features of R and give you a one-of-a-kind grounding in data science…
You will go all the way from carrying out data reading & cleaning to finally implementing powerful neural networks and deep learning algorithms and evaluating their performance using R.
Among other things:
•You will be introduced to powerful R-based deep learning packages such as H2O.
•You will be introduced to important concepts of machine learning without the jargon.
•You will learn how to implement both supervised and unsupervised algorithms using the H2O framework
•Identify the most important variables.  
•Implement both Artificial Neural Networks (ANN) and Deep Neural Networks (DNNs) with the H2O framework
•Work with real data within the framework

NO PRIOR R OR STATISTICS/MACHINE LEARNING KNOWLEDGE IS REQUIRED:
You’ll start by absorbing the most valuable R Data Science basics and techniques. I use easy-to-understand, hands-on methods to simplify and address even the most difficult concepts in R.
My course will help you implement the methods using real data obtained from different sources. Many courses use made-up data that does not empower students to implement R based data science in real-life.
After taking this course, you’ll easily use the data science package H2O to implement novel deep learning techniques in R. You will get your hands dirty with real-life data, including real-life imagery data which you will learn to pre-process and model
You’ll even understand the underlying concepts to understand what algorithms and methods are best suited for your data.
We will also work with real data and you will have access to all the code and data used in the course. 
JOIN MY COURSE NOW!

What can you learn from this course?

✓ Be Able To Harness The Power Of R For Practical Data Science
✓ Learn the Important Concepts Associated With Supervised and Unsupervised Learning
✓ Implement Supervised and Unsupervised Learning on Real Life Data With the Powerful H2O Package in R
✓ Implement Unsupervised Learning on Real Life Data With the Powerful H2O Package in R
✓ Implement Artificial Neural Networks (ANN) on Real Life Data With the Powerful H2O Package in R
✓ Implement Deep Neural Networks (DNN) on Real Life Data With the Powerful H2O Package in R

What you need to start the course?

• Be Able To Operate & Install Software On A Computer
• Prior Exposure To Common Machine Learning Terms Such As Unsupervised & Supervised Learning
• Prior Exposure To What Neural Networks Are & What They Can Be Used For
• Be Able to Install Packages in R

Who is this course is made for?

• People Wanting To Master The R & R Studio Environment For Data Science
• Anyone With Prior Exposure To Common Machine Learning Concepts Such As Supervised Learning
• Students Wishing To Learn The Implementation Of Neural Networks On Real Data In R
• Students Wishing To Learn The Implementation Of Basic Deep Learning Concepts In R
• Students Wishing To Implement Supervised and Unsupervised Learning on Real Life Data in R
• Students Wishing to Master a Powerful Data Science Framework, H2O For Machine Learning in R

Are there coupons or discounts for Complete Machine Learning and Deep Learning With H2O in R ? What is the current price?

The course costs $17.99. And currently there is a 82% discount on the original price of the course, which was $99.99. So you save $82 if you enroll the course now.
The average price is $13.6 of 749 Machine Learning courses. So this course is 32% more expensive than the average Machine Learning course on Udemy.

Will I be refunded if I'm not satisfied with the Complete Machine Learning and Deep Learning With H2O in R course?

YES, Complete Machine Learning and Deep Learning With H2O in R has a 30-day money back guarantee. The 30-day refund policy is designed to allow students to study without risk.

Are there any financial aid for this course?

Currently we could not find a scholarship for the Complete Machine Learning and Deep Learning With H2O in R course, but there is a $82 discount from the original price ($99.99). So the current price is just $17.99.

Who will teach this course? Can I trust Minerva Singh?

Minerva Singh has created 46 courses that got 16,390 reviews which are generally positive. Minerva Singh has taught 82,987 students and received a 4.5 average review out of 16,390 reviews. Depending on the information available, we think that Minerva Singh is an instructor that you can trust.
Bestselling Instructor & Data Scientist(Cambridge Uni)
I completed a PhD (University of Cambridge, UK) in 2017 where I focussed on implementing data science techniques for quantifying the impact of forest loss on tropical ecosystems. I hold an MPhil (School of Geography and Environment) and an MSc (Department of Engineering) from Oxford University. I have more than 10 year’s experience in conducting academic research (published in high level peer-reviewed international scientific journals such as PLOS One) and advising both non-governmental and industry stakeholders in data science, deep learning and earth observation (EO) related topics. I have a strong track record in implementing machine learning, data visualization, spatial data analysis, deep learning and natural language processing tasks using both R and Python. In addition to being educated at the best universities in the world, I have honed my statistical and data analysis skills through many MOOCs, including The Analytics Edge (R based statistics and machine learning course offered by EdX), Statistical Learning (R-based Machine Learning course offered by Stanford online) and the IBM Data Science Professional certificate Track. I specialise in a variety of topics ranging from deep learning (Tensorflow, Keras) to machine learning to spatial data analysis (including EO data processing), data visualizations, natural language processing, financial analysis among others. I have acted as a peer reviewer on highly regarded academic journals such as Remote Sensing and given guest lectures on prestigious forums such as Open Data Science Conference (ODSC).
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8.8

Classbaze Grade®

7.0

Freshness

9.5

Popularity

9.2

Material

Platform: Udemy
Video: 4h 21m
Language: English
Next start: On Demand

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