Get yourself trained on Machine Learning with with this Online Training Machine Learning with R.
Online Training Machine Learning with R
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 Rprogramming, and you can learn Rprogramming 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 tree, knn, neural network, linear regression, and evaluate your models very soon after learning the course. You can take the course as follows, and you can take a 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 future)- Machine Learning with R (Modeling and Evaluation)ContentGetting StartedGetting Started 2Getting Started 3Data Mining ProcessDownload Data setRead Data setSome ExplanationsSimple Linear RegressionBuild Linear Regression ModelsPredict Linear Regression ModelsKMeans ClusteringKMeans Clustering in RAgglomeration ClusteringAgglomeration Clustering in RDecision Tree ID3 ALgorithmDecision Tree in R:Split train and test setDecision Tree in R:Train Decision TreeDecision Tree in R:Predict Decision TreeKNNClassificationTrain KNN in RPredict KNN in RNaive Bayes ClassificationNaive Bayes in RNeural Network ClassificationNeural Network in RWhat Algorithm to Use?Model EvaluationModel Evaluation using R for ClassificationModel Evaluation using R for Regression
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As a society, we spend hundreds of billions of dollars measuring the return on our financial assets. Yet, at the same time, we still haven’t found convincing ways of measuring the return on our investments in developing people.
And I get it: If my bank account pays me 1% a year, I can measure it to the penny. We’ve been collectively trained to expect neat and precise ROI calculations on everything, so when it’s applied to something as seemingly squishy as how effectively people are learning in the workplace, the natural inclination is to throw up our hands and say it can’t be done. But we need to figure this out. In a world where skills beat capital, the winners and losers of the next 30 years will be determined by their ability to attract and develop great talent.
Fortunately, corporate learning & development (L&D), like most business functions, is evolving quickly. We can embrace some level of ambiguity and have rigor when measuring the ROI of learning. It just might look a little different than an M.B.A. would expect to see in an Excel model.