Machine Learning

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Machine Learning is a relatively new branch of Statistics (at least by name), and focuses on using statisical patterns and probabilities to infer (or basically, take a highly educated guess) future patterns and/or desired program outputs, based on the statistics surrounding particular inputs.


Algorithms

Bayesian Models

Bayesian models, also known as Bayes algorithm, is a basic method of infering outputs based on known/provided inputs. It breaks up probabilities of outcomes into grids of percentage of likelihood of occurence, providing a somewhat reliable but still quite basic method to evaluate (or learn) about what outputs are best for a given situation.


Neural Networks

Transformers




Tools

Weka

Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.

Zeitgeist

As a tool for providing desktop activity awareness, Zeitgeist runs as a service which logs users's activities and events, anywhere from files opened to websites visited and conversations.

Google

Cloud ML

PredictionIO

[4] [5]

Seldon


Resources


Tutorials


External Links


References

  1. Google Cloud Machine Learning - now open to all with new professional services and education programs: https://cloud.google.com/blog/big-data/2016/09/google-cloud-machine-learning-now-open-to-all-with-new-professional-services-and-education-programs
  2. Google Cloud Platform sets a course for new horizons: http://cloudplatform.googleblog.com/2016/09/Google-Cloud-Platform-sets-a-course-for-new-horizons.html
  3. Google announces tools to "democratize" machine learning: http://www.zdnet.com/article/google-announces-tools-to-democratize-machine-learning/
  4. Winning the Ride-Sharing Startup Battle with Personalization -- A Java How-to: http://blog.prediction.io/winning-ride-sharing-startup-battle-personalization-java/#.UnJnABA2Y1p
  5. PredictionIO -- Quick Start - Recommendation Engine Template: https://predictionio.apache.org/templates/recommendation/quickstart/
  6. Getting to Know Deep Java Library (DJL): https://www.infoq.com/articles/djl-deep-learning-java/

See Also

Statistics | AI | Robotics | Semantic Web | Big Data | Data Science | Analytics | Recommender Systems | Personalization | Advertising | Marketing