The Need of Recognizing the Value of Machine Learning

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Machine learning is an approach to artificial intelligence that’s focused on making machines which can learn without being explicitly programmed. As machine learning becomes increasingly valuable and the technology matures, more businesses will start using the cloud to offer machine learning as a service (MLaaS). This will allow a wider range of organizations to take advantage of machine learning without making large hardware investments or training their own algorithms. And the more you feed it, the “smarter” it gets in terms of what it is able to predict.


  • Machine Learning in Simple Terms-
While artificial intelligence (AI) is the broad science of mimicking human abilities, machine learning is a specific subset of AI that trains a machine how to learn.
  • Machine Learning Applications-
  1. The self-driving Google car
  2. Cyber fraud detection
  3. Online recommendation engines—like friend suggestions on Facebook
  4. Netflix showcasing the movies and shows
  • How Businesses Are Using Machine Learning Technologies-
Machine learning technology and the artificial intelligence (AI) are everywhere in the news, but it’s not just hype — they are the technologies your competitors, suppliers and partners are already adopting and getting value from. Organizations are finding profitable opportunities to grow their business by identifying the precise models to avoid unknown risks. The use of algorithms to build a model is helping organizations to bridge the gap between their products and users with better decisions and least human intervention. Most industries with enormous volumes of data have recognized the value of machine learning.
Conclusion-
Machine learning is still a complex beast. Away from simplified playgrounds, there’s not much you can do with neural networks yourself unless you have a strong background in coding. In machine learning, unsupervised algorithms are employed to make predictions from datasets when only input data is available without corresponding output variables.

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