Course Teacher: Kate Alison, Georg Müller
Language: English
Description:
HERE IS WHY YOU SHOULD TAKE THIS COURSE:
This course might be your full information to unsupervised studying and clustering utilizing R-programming language and JavaScript.
Not like different programs, it affords NOT ONLY the guided demonstrations of the R-scripts but in addition covers theoretical background that can can help you FULLY UNDERSTAND & APPLY UNSUPERVISED MACHINE LEARNING (Okay-means, Hierarchical clustering) in R.
This course additionally covers all of the major elements of sensible and extremely utilized information science associated to unsupervised machine studying and clustering methods. Thus, in case you take this course, you’ll save plenty of time & cash on different costly supplies within the R based mostly information science area.
On this age of massive information, corporations throughout the globe use R and Google Cloud Computing Providers to investigate large volumes of knowledge for enterprise and analysis. By turning into proficient in unsupervised studying in R, you may give your organization a aggressive edge and increase your profession to the subsequent degree. As well as, you should have an opportunity to check the facility of cloud computing with Google providers (i.e. Earth Engine) for a real-world software of unsupervised Okay-means studying for mapping functions.
THIS COURSE HAS 8 SECTIONS COVERING EVERY ASPECT OF UNSUPERVISED MACHINE LEARNING: THEORY & PRACTISE
– Absolutely perceive the fundamentals of Machine Studying, Cluster Evaluation & Unsupervised Machine Studying from concept to apply
– Harness functions of unsupervised studying (cluster evaluation) in R and with Google Cloud Providers
– Machine Studying, Supervised Studying, Unsupervised Studying in R
– Full two unbiased initiatives on Unsupervised Machine Studying in R and utilizing Google Cloud Providers
– Implement Unsupervised Clustering Strategies (k-means Clustering and Hierarchical Clustering and many others)
– and MORE
NO PRIOR R OR STATISTICS/MACHINE LEARNING / R KNOWLEDGE REQUIRED:
You’ll begin by absorbing essentially the most worthwhile R Knowledge Science fundamentals and methods. I take advantage of easy-to-understand, hands-on strategies to simplify and deal with even essentially the most troublesome ideas in R.
My course will enable you implement the strategies utilizing actual information obtained from totally different sources, together with implementing a real-life mission on the cloud computing platform of Google. Thus, after finishing my unsupervised information clustering course in R, you’ll simply use totally different information streams and information science packages to work with actual information in R.
I may even offer you the all scripts and information used within the course.
In case it’s your first encounter with R, don’t fear, my course a full introduction to the R & R-programming on this course.
This course is totally different from different coaching sources. Every lecture seeks to reinforce your information science and clustering expertise (Okay-means, Hierarchical clustering, weighted-Okay means, Warmth mapping, and many others) in a demonstrable and easy-to-follow method and offer you virtually implementable options. You’ll be capable to begin analyzing totally different streams of knowledge on your initiatives and achieve appreciation out of your future employers together with your improved machine studying expertise and information of the innovative information science strategies.
The course is right for professionals who want to make use of cluster evaluation, unsupervised machine studying, and R of their discipline.
One vital a part of the course is the sensible workouts. You can be given some exact directions and datasets to run Machine Studying algorithms utilizing the R and Google Cloud Computing instruments.
JOIN MY COURSE NOW!
Who this course is for:
- The course is right for professionals who want to make use of cluster evaluation, unsupervised machine studying and R of their discipline.
- Everybody who wish to study Knowledge Science Functions In The R & R Studio Atmosphere
- Everybody who wish to study concept and implementation of Unsupervised Studying On Actual-World Knowledge
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