Challenges Faced By Businesses in Adopting Machine Learning

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Challenges Faced By Businesses in Adopting
Machine Learning
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• Machine Learning is important for the future
  industry because it saves human effort and time.
• Machine studies from existing data using
  algorithms that iteratively learn from the data
  set.
• Machine learning allows computers to find hidden
  insights without being explicitly programmed
  where to look.

• Different Challenges Faced By Businesses in
  Adopting Machine Learning
• Inaccessible Data and Sensitive Data Security
• Infrastructure Requirements for Experimentation
  and Testing
• Inflexible Business Models

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Inaccessible Data and Sensitive Data Security

• Presence of raw data is difficult to gather.
• Segregating sensitive and insensitive data is
  indispensable to implementing Machine Learning
  properly and efficiently.
• Organizations need to store the confidential data
  by encrypting it and storing it in other servers
  where the data is completely secured

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Infrastructure Requirements for Experimentation
and Testing

• Appropriate infrastructure can help in the
  testing of diverse tools.
• Frequent tests should also be permissible to
  develop the desired outcomes.
• Organizations can give their data to different
  enterprises and ask for their response.

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Inflexible Business Models

• Employing Machine Learning efficaciously needs
  one to change infrastructure, attitude, and also
  needs proper and appropriate skill-set.
• Employing Machine Learning doesnt guarantee
  success. Experimentations need to be done if one
  idea doesnt work

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