MACHINE LEARNING

WHAT IS MEANT BY MACHINE LEARNING
 

      Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed.

WHAT ARE THE BEST PROGRAMMING LANGUAGES 

  1.         1.Python Highly rated machine-learning repositories.
  2.        .2.C++ Highly rated machine-learning repositories.
  3.         3.JAVA SCRIPT - highly rated machine learning


  5.         4.Java 
  6.         5.C# 
  7.         6.Julia
  8.         7.Shell
  9.         8.R

  11. WHAT IS MACHINE LEARNING EXAMPLES
  12.       The  few examples of machine learning that we use everyday and perhaps have no idea that they are driven by   ML.Siri Alex,a Google Now are some of the popular examples of virtual personal assistants. As the name suggests, they assist in finding information, when asked over voice.

MACHINE LEARNING IS GOOD FOR 
  
            The iterative aspect of machine learning is important because as models are exposed to new data, they are able to independently adapt. They learn from previous computations to produce reliable, repeatable decisions and results. It's a science that's not new – but one that has gained fresh momentum.

BASICS OF MACHINE LEARNING

         Every machine learning algorithm has three components: Representation: how to represent knowledge. Examples include decision trees, sets of rules, instances, graphical models, neural networks, support vector machines, model ensembles and others. Evaluation: the way to evaluate candidate programs (hypotheses).

WHAT FIELD IN MACHINE LEARNING
 
      Machine Learning is built on the field of Mathematics and Computer Science. Specifically, machine learning methods are best described using linear and matrix algebra and their behaviours are best understood using the tools of probability and statistics.

IS MACHINE LEARNING IS HARD?
   There is no doubt the science of advancing machine learning algorithms through research is difficult. It requires creativity, experimentation and tenacity. Machine learning remains a hard problem when implementing existing algorithms and models to work well for your new application.

IS MACHINE LEARNING IS GOOD OR BAD
          Poor data quality is enemy number one to the widespread, profitable use of machine learning. The quality demands of machine learning are steep, and bad data can rear its ugly head twice both in the historical data used to train the predictive model and in the new data used by that model to make future decisions.

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