Once
the exclusive domain of academics and corporations with large research budgets,
intelligent applications that learn from data and user input are becoming more
common. The need for machine-learning techniques like clustering, collaborative
filtering, and categorization has never been greater, be it for finding
commonalities among large groups of people or automatically tagging large
volumes of Web content. The Apache Mahout project aims to make building
intelligent applications easier and faster. Mahout co-founder Grant Ingersoll
introduces the basic concepts of machine learning and then demonstrates how to
use Mahout to cluster documents, make recommendations, and organize content.
Apache
Mahout is an Apache TLP project to build powerful scalable machine learning
tools for use on analyzing big-data on distributed manner. Machine learning is
the discipline of artificial intelligence that enables to learn on data, spam
filtering and natural language processing. Apache mahout enable clustering,
dimensionality reduction and miscellaneous.
Machine
learning is a subfield of artificial intelligence concerned with techniques
that allow computers to improve their outputs based on previous experiences.
The field is closely related to data mining and often uses techniques from
statistics, probability theory, pattern recognition, and a host of other areas.
Although machine learning is not a new field, it is definitely growing. Many
large companies, including IBM®, Google, Amazon, Yahoo!, and Facebook, have
implemented machine-learning algorithms in their applications. Many, many more
companies would benefit from leveraging machine learning in their applications
to learn from users and past situations.
Machine learning uses run the gamut from game playing to fraud detection to stock-market analysis. It's used to build systems like those at Netflix and Amazon that recommend products to users based on past purchases, or systems that find all of the similar news articles on a given day. It can also be used to categorize Web pages automatically according to genre (sports, economy, war, and so on) or to mark e-mail messages as spam.
Machine learning uses run the gamut from game playing to fraud detection to stock-market analysis. It's used to build systems like those at Netflix and Amazon that recommend products to users based on past purchases, or systems that find all of the similar news articles on a given day. It can also be used to categorize Web pages automatically according to genre (sports, economy, war, and so on) or to mark e-mail messages as spam.
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