Mining Massive Datasets (2016) by Coursera

Mining Massive Datasets (2016) by Coursera

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Description:

We introduce the participant to modern distributed file systems and MapReduce, including what distinguishes good MapReduce algorithms from good algorithms in general. The rest of the course is devoted to algorithms for extracting models and information from large datasets. Participants will learn how Google’s PageRank algorithm models importance of Web pages and some of the many extensions that have been used for a variety of purposes.

We’ll cover locality-sensitive hashing, a bit of magic that allows you to find similar items in a set of items so large you cannot possibly compare each pair. When data is stored as a very large, sparse matrix, dimensionality reduction is often a good way to model the data, but standard approaches do not scale well; we’ll talk about efficient approaches. Many other large-scale algorithms are covered as well, as outlined in the course syllabus.

Internet Marketing Course

Digital marketing is the component of marketing that utilizes internet and online based digital technologies such as desktop computers,
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employing combinations of search engine optimization (SEO), search engine marketing (SEM), content marketing, influencer marketing, content automation,
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e–books, and optical disks and games have become commonplace. Digital marketing extends to non-Internet channels that provide digital media, such as television,
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