Online Training Data Science complete guide on Linear Algebra – DeepLearning by Udemy

Get yourself trained on Data Science complete with this Online Training Data Science complete guide on Linear Algebra – DeepLearning.

Online Training Data Science complete guide on Linear Algebra – DeepLearning

Interested in increasing your Machine Learning, Deep Learning expertise by effectively applying the mathematical skills ?Then, this course is for you.With the growing learners of Machine Learning , Data Science and Artificial intelligence.The Common mistake by a data scientist is Applying the tools without the intuition of how it works and behaves.Having the solid foundation of mathematics will help you to understand how each algorithms work, its limitations and its underlying assumptions.With this, you will have an edge over your peers and makes you more confident in all the applications of Machine Learning, Data Science and Artificial intelligenceAs a common saying:It always pays to know the machinery under the hood, rather than being a guy who is just behind the wheel with no knowledge about the car.Linear Algebra is one of the area where everyone agrees to be a starting point in learning curve of Machine Learning, Data Science and Artificial intelligence. Its basic elements Vectors and Matrices are where we store our data for input as well as output.Any operation or Processing involving storing and processing the huge number of data in Machine Learning, Data Science and Artificial intelligence, would mostly use Linear Algebra in the backend. Even Deep Learning and Neural Networks – Employs the Matrices to store the inputs like image, text etc. to give the state of the art solution to complex problems. Keeping in mind about the significance of Linear Algebra in Data Science career, we have tailor made this curriculum such that you will be able to build the strong intuition on the concepts in Linear Algebra without being lost inside the complex mathematics.At the end of this course, you will also learn, how the Famous Google PageRank Algorithm works, using the concepts of Linear Algebra which we will be learning in this course.In this course. you will not only learn analytically, you will see its working by running in Python as well. So, with this course, you will learn, build intuition and apply to some of the interesting real world applications.Click on the Enroll Button to start Learning.I look forward to see you in Lecture 1

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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.