Get yourself trained on Practical Neural Networks with this Online Training Practical Neural Networks & Deep Learning In R.
Online Training Practical Neural Networks & Deep Learning In R
YOUR COMPLETE GUIDE TO PRACTICAL NEURAL NETWORKS & DEEP LEARNING IN R: This course coversthe main aspectsof neural networks and deep learning. If you take this course, you can do away with taking other courses or buying books on R based data science. 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 neural networks and deep learning inR, 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 Singhand Iam an Oxford University MPhil (Geography and Environment) graduate. I recently finished aPhD at Cambridge University. I have +5 yearsofexperience 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 theredo not account for the multidimensional nature of the topic . This course will give you a robust grounding in the mainaspects of practical neural networks and deep learning.Unlike other R instructors, I dig deep into the data sciencefeatures of R and give you a one-of-a-kind grounding indata science… You will go all the way from carrying out data reading & cleaning to to finally implementing powerful neural networks and deep learning algorithms and evaluating their performanceusing R.Among other things:You will be introduced to powerful R-based deep learning packages such as h2o and MXNET. You will be introduced to deep neural networks (DNN), convolution neural networks (CNN) and recurrent neural networks (RNN). You will learn to apply these frameworks to real life data including credit card fraud data, tumor data, images among others for classification and regression applications.With this course, youll have the keys to the entire R Neural Networks and Deep LearningKingdom!NO PRIOR R OR STATISTICS/MACHINE LEARNING KNOWLEDGE IS REQUIRED:Youll start by absorbing the most valuable R Data Science basics and techniques. I useeasy-to-understand, hands-on methods to simplify and address even the most difficult concepts in R. My course willhelp youimplement the methods using real dataobtained 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, youll easily use data sciencepackages like caret, h2o, mxnetto work with real data in R…Youll 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!
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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.