Скачать или смотреть Explainable machine learning & model transparency – from "Machine Learning Leadership and Practice"

NEW BOOK: The AI Playbook by Eric Siegel. In his bestselling first book, Eric explained how machine learning works. Now, in The AI Playbook, he shows how to capitalize on it. A Next Big Idea Club Must Read. Info: http://www.bizML.com

From the course "The Power of Machine Learning", part of the three-course specialization, "Machine Learning Leadership and Practice – End-to-End Mastery".

Access this unique curriculum: http://www.machinelearning.courses

This expansive, end-to-end course series will empower you to launch machine learning. Accessible to business-level learners and yet vital to techies as well, it covers both the state-of-the-art techniques and the business-side best practices.

After three courses, you will be able to:

Lead ML: Manage or participate in the end-to-end implementation of machine learning

Apply ML: Identify the opportunities where machine learning can improve marketing, sales, financial credit scoring, insurance, fraud detection, and much more

Greenlight ML: Forecast the effectiveness of and scope the requirements for a machine learning project and then internally sell it to gain buy-in

Regulate ML: Manage ethical pitfalls, the risks to social justice that stem from machine learning

ABOUT THIS SPECIALIZATION OF THREE COURSES

Machine learning is booming. It reinvents industries and runs the world. According to the Harvard Business Review, machine learning is “the most important general-purpose technology of our era.”

But while there are so many how-to courses for hands-on techies, there are practically none that also serve business leaders – a striking omission, since success with machine learning relies on a very particular business leadership practice just as much as it relies on adept number crunching.

This specialization fills that gap. It empowers you to generate value with machine learning by ramping you up on both the technical side and the business side – both the cutting edge modeling algorithms and the project management skills needed for successful deployment.

NO HANDS-ON AND NO HEAVY MATH. Rather than a hands-on training, this specialization serves both business leaders and burgeoning data scientists alike with expansive, holistic coverage of the state-of-the-art techniques and business-level best practices. There are no exercises involving coding or the use of machine learning software.

BUT TECHNICAL LEARNERS SHOULD TAKE ANOTHER LOOK. Before jumping straight into the hands-on, as quants are inclined to do, consider one thing: This curriculum provides complementary know-how that all great techies also need to master. It contextualizes the core technology, guiding you on the end-to-end process required to successfully deploy a predictive model so that it delivers a business impact.

IN-DEPTH YET ACCESSIBLE. Brought to you by industry leader Eric Siegel – a winner of teaching awards when he was a professor at Columbia University – this specialization stands out as one of the most thorough, engaging, and surprisingly accessible on the subject of machine learning.

WHAT YOU'LL LEARN: How ML works, how to report on its ROI and predictive performance, best practices to lead an ML project, technical tips and tricks, how to avoid the major pitfalls, whether true AI is coming or is just a myth, the risks to social justice that stem from ML.

DYNAMIC CONTENT. Across this range of topics, this specialization keeps things action-packed with case study examples, software demos, stories of poignant mistakes, and stimulating assessments.

VENDOR-NEUTRAL. This specialization includes several illuminating software demos of machine learning in action using SAS products, plus one hands-on exercise using Excel or Google Sheets. However, the curriculum is vendor-neutral and universally-applicable. The contents and learning objectives apply, regardless of which machine learning software tools you end up choosing to work with.

WHO IT’S FOR. This concentrated entry-level program is totally accessible to business-level learners – and yet also vital to data scientists who want to secure their business relevance. It’s for anyone who wishes to participate in the commercial deployment of machine learning, no matter whether you’ll do so in the role of enterprise leader or quant. This includes business professionals and decision makers of all kinds, such as executives, directors, line of business managers, and consultants – as well as data scientists.

LIKE A UNIVERSITY COURSE. These three courses are also a good fit for college students, or for those planning for or currently enrolled in an MBA program. The breadth and depth of this specialization is equivalent to one full-semester MBA or graduate-level course.

Access the full program: http://www.machinelearning.courses