Learn Recommender Systems with Machine Learning and AI

My latest course from Sundog Education is “Building Recommender Systems with Machine Learning and AI” – I’m really proud of this one.

Recommender systems are core to the mission of the biggest tech employers. Amazon, where I worked for 9 years, uses them to get new items in front of customers that appeal to their unique, individual interests – and it’s been reported that Amazon attributes over 20% of its revenue to recommender systems. Netflix has a saying that “everything is a recommendation” – your Netflix home page is nothing more than a big collection of recommender engines that are trying to get content that appeals to you in front of you. And YouTube relies on recommender systems to help you choose what to watch next. These are hugely important systems to these companies, and people who understand how they work are in high demand.

I’ve not only covered the traditional approaches to recommender systems involving collaborative filtering in this course, but also more recent approaches using matrix factorization, and deep learning with artificial neural networks. It even includes several “bleeding edge alert” features where brand-new research in the field is covered – you’ll be up to date on the latest developments in the field after taking this course.

Like all of my courses, it’s very hands-on and includes many activities and exercises you can try on your own, using the Python programming language. It includes 9 1/2 hours of video content and over 100 lectures.

Check it out! Follow this Udemy link to learn about recommender systems for $15: https://www.udemy.com/building-recommender-systems-with-machine-learning-and-ai/?couponCode=RECSYS15

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