Machine Learning is playing an ever more prominent part in our daily lives. We live in an interconnected world where there is access to vast and diverse stores of historical data, abundant computing power for intense number-crunching, and a growing body of learning algorithms. Together, they make it possible for computers to do the following and more:

  • Make decisions and predictions
  • Perform tasks better as they gain exposure and experience with them
  • Learn rules on the basis of background knowledge, examples and hypotheses
  • Discover clusters in a large set of observations and figure out what’s meaningful with no prior knowledge
  • Model the way humans learn using neural network computing
  • Apply genetic and evolutionary principles to assess  the fitness of a population to perform a task
  • Predict behavior in complex, real world scenarios over the short and long term

Areas where you’ll find machine learning powering solutions include:

  • Adaptive applications
  • Analysis of public sentiment
  • Autonomous robotics
  • Bio and chemical informatics
  • Computer vision, object and facial recognition
  • Data mining
  • Dynamic software development
  • Financial markets analysis
  • Gaming and simulation
  • Handwriting and speech recognition
  • Machine perception
  • Medical diagnostics
  • Monitoring of structural integrity
  • Natural language processing
  • Pattern recognition
  • Recommender systems
  • Search

This blog is dedicated to creating awareness of the practical applications of machine learning. You can look forward to perspectives from researchers in academia, engineers of machine learning software, as well as industry and business experts who are driving the evolution of this field.

We welcome contributions from interested people. Please send an email to blog@MachineLearningSoftware.org with your expertise, ideas or leads on information about this area of knowledge.


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