Understanding the Differences Between AI, ML And DL

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Understanding the Differences Between AI, ML And
DL
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• Popular terms we often hear nowadays, artificial
  intelligence, machine learning and deep learning
  are all closely related, that much is true, but
  there are some important differences between
  them. Helping companies streamline their
  processes and make their systems more efficient,
  lets look at the differences in a little more
  detail
• Artificial intelligence
• Enabling machines to think without the need for
  any input from humans, this broad area of
  computer science adds human intelligence to
  machines, and its systems are classified by how
  well they can replicate human behaviors, what
  hardware they use, how can they be used and the
  theory of mind. All AI systems fall into one of
  the following three categories

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• Artificial narrow intelligence
• Artificial general intelligence
• Artificial super intelligence
• Machine learning
• Using statistical algorithms to build systems
  that can learn automatically and improve from
  experiences without being programmed, machine
  learning is best thought of as a subset of
  artificial intelligence.

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• Search engines such as Google and Yahoo, voice
  assistants like Alexa, and recommendation systems
  on Netflix, are all examples of machine learning
  that many of us use every day, and without really
  giving the technology behind it a second thought.
  Machine learning works by training algorithms
  with the input of big data, and enabling them to
  learn more about the information being processed.
• The algorithms used in machine learning are
  generally placed into the following three
  categories

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• Supervised
• Unsupervised
• Reinforcement learning
• Deep learning
• Inspired by the way a human brain filters
  information, deep learning is a technique that
  uses machine learning to learn from examples.
  Processing information in a similar way to the
  human brain, it helps filter input data from a
  computer model, to better predict and classify
  information.

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• Because its processes mimic human thoughts, its
  technology is typically used in applications
  commonly used by humans, such as driverless cars,
  in which deep learning enables the vehicle to
  recognize road signs and know the difference
  between certain obstacles, such as a person or a
  lamppost. Using neural network architectures,
  deep learning methods are sometimes known as deep
  neural networks.
• There are three fundamental network architectures
  involved in deep learning, as shown below

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• Convolutional neural networks
• Recurrent neural networks
• Recursive neural networks
• Many industries have already begun integrating
  machine learning technology into all stages of
  their production, and with more and more
  technology driven and powered by AI, businesses
  in all sectors can streamline their processes,
  predict problems before they occur, serve their
  customers better, and ultimately, give their
  bottom lines a much-needed boost.
• To know more about how AI, machine and deep
  learning could help your business, reach out to a
  reputable tech company today, who can help bring
  your company in line with others who are already
  embracing its many benefits.

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• Intelliprise commits to empower organizations
  with cutting edge solutions. Intelliprise LLC is
  based in Indianapolis, IN and offers holistic
  Enterprise solutions, technologies, and systems
  integration for over 200 companies worldwide,
  ranging from startups to Fortune 1000 companies.
  Many of the largest companies outsource their
  business needs to Intelliprise, including leaders
  in retail, travel, e-commerce, education,
  hospitality, manufacturing, consumer goods,
  logistics, SCM, lifestyle, non-profits, and BFSI.