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Machine Learning Infrastructure Challenges

Trusted and reliable relational database management systems can fail completely under the load and variety of data that organizations seek to collect and analyze today. Some infrastructure challenges include storage, computation, and…

Machine Learning in the Analytic Landscape

Machine learning first appeared in computer science research in the 1950s. So why, after all these decades, has it become so popular? The easy answer is that both the data storage and the data processing capacities have grown tremendously,…

Building the LinkedIn Data Science Team

Reference: Building Data Science Teams ,The Skills, Tools, and Perspectives Behind Great Data Science Groups - DJ Patil I’m proud of what we’ve accomplished in building the LinkedIn data team. However, when we started, it didn’t look…

Who is using Machine Learning?

Most industries working with large amounts of data have recognized the value of machine learning technology. By gleaning insights from this data – often in real time – organizations can work more efficiently or gain an advantage over…

What are some popular machine learning methods?

Two of the most widely adopted machine learning methods are supervised learning and unsupervised learning – but there are also other methods of machine learning. Here's an overview of the most popular types. Supervised learning algorithms…

The Roles of a Data Scientist

In every organization I’ve worked with or advised, I’ve always found that data scientists have an influence out of proportion to their numbers. The many roles that data scientists can play fall into the following domains. Decision sciences…

15 Free Machine Learning Books

The following Machine Learning list of books are free online, review them and download some of them today! Information Theory, Inference, and Learning Algorithms - Textbook by David J.C. MacKay - Published by Cambridge University Press…

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