Get yourself trained on A Beginner’s Guide with this Online Training A Beginner’s Guide to Machine Learning (in Python).
Online Training A Beginner’s Guide to Machine Learning (in Python)
In this course, you will learn the basics of Machine Learning andData Mining; almost everything you need to get started. You will understand what Big Data is and what Data Science and DataAnalytics is. You will learn algorithms such as Linear Regression, Logistic Regression,Support Vector Machine, K-Nearest Neighbor, Decision Trees, and Neural Networks. You’ll also understand how to combine algorithms into ensembles. Preprocessing data will be taught andyou will understand how to clean your data, transform it, how to handle categorical features, and how to handle unbalanced data. By the end of this course, you will understand the ABCs of Machine Learningand be able to implement what you’ve learnt on your own, more specifically, be able to implement what you’ve learnt on Python. There is no ideal student as there are no prior requirements needed – everybody is welcome!!Please feel free to ask me any question! Don’t like the course? Ask for a 30-day refund!!Real Testaments -->1) “Excellent course!! Dana is very knowledgeable about Machine Learning, and is able to present the concepts and practices in a way that is easy to understand, along with actionable exercises to implement and practice. The presentation is very detailed and direct. A topic is introduced, explained, displayed with example and then we began implementing it.” — Joseph, 5 star rating2) “The instructor gives a very basic explanation for complicated material. that makes it very easy for me to understand given that I already studied that in a master class but I understand it better here. Thank you” — Fatimah, 5 star rating3) “I think it was a very useful begginner’s guide to Machine Learning using Python. I learned a lot !. Thanks” — Hernan, 4 star rating
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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.