MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 39 lectures (4h 21m) | Size: 2.73 GB
H2O:Master Powerful R Package For Machine Learning, Artificial Neural Networks (ANN) and Deep Learning
What you’ll learn:
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
Requirements
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
Description
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.
Who this course is 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
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