Get yourself trained on The Visual Guide with this Online Training The Visual Guide on How Neural Networks Learn from Data.
Online Training The Visual Guide on How Neural Networks Learn from Data
Course Achievements (February 2018):+450WorldwideStudents enrolledTrophy Awards for Key Section Achievements!Some Student Reviews are:”Very structured and logical” (July 2018).”Great Explanation of NN. Will definitely recommend to others.” (April 2018)”Enlightening overview of how neural networks operate mathematically.” (March 2018).”An Excellent Course” (February 2018).”The NN is a Complex topic and the instructor explains the NN very clearly. The demonstration shows how NN learns from data in a very precise way. I highly recommend this course.” (January 2018).”I just loved this course. The course is very well taught and is divided in easy-to-digest units.”(December 2017).More Student Reviews:”Highly visual. Good explaining. Easy to grasp. I can’t praise this work enough! Absolutely brilliant teaching material”(November 2017)”excellently delivered step by step .. visually learning is very clear and easily understandable.”(November 2017)”Very clear and straight forward. Course is a great first step to understand the structure of a NN, and how it works.”(November 2017)”The course is interesting because it explains the basic mathematics of a neural network in a very simple and intuitive way.”(October 2017)”Very clear, very interesting and keeps u motivated to learn more.” (September 2017)”This is the best example and explanation I could find about the internal working of NN (…)”(August 2017)”This is a unique way of explaining and illustrating the operation of a simple ANN.” (July 2017)”Excellent course! It teaches you the basic of Neural Network in an easy to understand way (…)” (June 2017)”Great starting point to learn ANNs!” (June 2017)”v[ery] good explaination” (May 2017)Hi. Thanks for showing interest in this course!What makes this course special:Step-by-Step Neural Network Learning Process,Master topics like Fundamentals, Objectives, Required Datasets, Weights, Biases, Nodes, Activation functions, Feed-Forward Passes, Predictions, Losses, Gradient Descent, Learning, Backpropagation and more!Plus, personalized feedback and help. You ask, Ianswer directly!This is your BEST resource for Neural Networks (NN) learning! A must for understanding special concepts and not get lost in computing your own NNs: First:You’ll start the Neural NetworksPrimer with Fundamentals, Objectives, Data and more:Learn concepts using analogies for maximum learning, so you will be fully covered.Learning how NNs learn will be easy with this Primer under your sleeve! Second:You’ll continue the NN Primer with Learning, Backpropagation and Predictions and more topicsIn aneasyandintuitiveway,you will understand how they work,This is fundamental in the NN Learning Process.At the end of this section,youwill have mastered the NN Primer! Now, you are ready for the Step-by-Step (in-Motion) sections! Third: You’ll start the in-Motion section with Inputs, Weights, Biases, Activations,Nodes and Feed-Forward Passes:See how they work inside an NN,Step-by-step templates, so you can follow every detail,These files will be dynamic, so you’ll understand how NNs work as numbers will be updated on-the-fly and right in front of your eyes. Forth:You’ll continue withthe in-Motionsection with NN Learning, Backpropagation, Tuning and Prediction:You will understand how NNs learn from the data.This all part of the dynamictemplates you get to keep.You’ll do several examples along the way for maximum learning.Lastly, you’ll see what NNs do to make the best predictions. Fifth:You’ll finish the in-Motion section by doing a complete rundown on everyting you’ve learned so far:You’ll see how all NN inner componentswork for learning and prediction.Pay close attention at how all parts adjust, making the NN learn in front of your eyes.After this section, you will be fully versed on how NNs learn! Sixth:I will devote a section for moreadditional knowledge and resources for continous learning. And then, I will conclude with some Final Words.What are the Requirements?Theonly thingyou’ll need for this course is: Excel and PowerPoint: It is that easy!You will also need to bring your Basic Maths too,If you bring your Calculus (Derivatives) knowledge, that will be a big plus for you (but not required),What are some of the Benefits?As it is usual in my courses, you will get all files and spreadsheets for all lectures.This way you can replicate everything I do immediately after each lecture.Neural Networks are the new thing today.With it, you can explore and engage Artificial Intelligence, which I recommend you to dive in as it’s part of the future.Plus, it’s very rewarding and fun too!New content coming in the near future, let me know yout thoughts.Lastly, you canpostquestions or doubts, and Ill answer to you personally.I hope you find this course as useful as I have creating it!Ill see you inside,-M.A. Mauricio M.
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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.