Get yourself trained on Random Forest Algorithm with this Online Training Random Forest Algorithm in Machine Learning.
Online Training Random Forest Algorithm in Machine Learning
Random Forest Algorithm in Machine Learning:Machine learning is a scientific discipline that explores the construction and study of algorithms that can learn from data. Such algorithms operate by building a model from example inputs and using that to make predictions or decisions, rather than following strictly static program instructions. Machine learning is closely related to and often overlaps with computational statistics; a discipline that also specializes in prediction-making.Through this training we are going to learn and apply how the random forest algorithm works and several other important things about it.The course includes the following;1) Extract the Data to the platform.2) Apply data Transformation.3) Bifurcate Data into Training and Testing Data set.4) Built Random Forest Model on Training Data set.5) Predict using Testing Data set.6) Validate the Model Performance.7) Improve the model Performance using Random Forest.8) Predict and Validate Performance of Model.
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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.