The year: 1998.  The size of the web: 150 million pages.  The problem: information retrieval.  How do you find the "best" web pages to return in response to a query?  A graduate student named Larry Page had an idea for how it could be done better and created a search engine as a research project.  That search engine was called Google.

The year: 1998. The size of the web: 150 million pages. The problem: information retrieval. How do you find the "best" web pages to return in response to a query? A graduate student named Larry Page had an idea for how it could be done better and created a search engine as a research project. That search engine was called Google.

The year: 1998. &nbsp;The size of the web: 150 million pages. &nbsp;The problem: information retrieval. &nbsp;How do you find the "best" web pages to return in response to a query? &nbsp;A graduate student named Larry Page had an idea for how it could be done better and created a search engine as a research project. &nbsp;That search engine was called Google.

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Linear Digressions is a podcast about machine learning and data science.  Machine learning is being used to solve a ton of interesting problems, and to accomplish goals that were out of reach even a few short years ago.

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Linear Digressions is a podcast about machine learning and data science. Machine learning is being used to solve a ton of interesting problems, and to accomplish goals that were out of reach even a few short years ago.

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