Key Difference Between Data Science

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Key Difference Between Data Science And
Machine Learning
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Table Of Content

1. Basic Concept
2. Benefits
3. Applications
4. Top Tools

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Basic Concept

• The extraction and analysis of important
  data-related details are called data science.
  It covers the techniques for visualizations,
  cleaning, analytics, data mining, and creating
  useful insights.

Machine learning is the element of data science
that allows a system to process datasets
automatically but without human involvement.
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Benefits

1. Machine learning helps with marketing and
   predicting exact sales.
2. Useful for making a precise medical diagnosis
3. Helping the removal of data duplication and
   errors
4. Sensitivity to spam detection
5. Make the right product recommendations.

1. Data science helps in identifying and modifying
   target audiences.
2. Make sure there is improved communication
   between service providers and users.
3. Enhanced risk estimates and increased business
   value.

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Applications

• Machine Learning
• Video surveillance with a virtual personal
  assistant.
• Monitoring for online fraud.
• Using social media.
• Filtering email for spam and malware Operational
  client support.
• Product suggestion.

• Data Science
• Fraud and Risk Detection.
• Autonomous Vehicles.
• Image Identification.
• Speech Recognition.
• Routing an airline.
• Search engines on the internet.

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Top Tools
Data Science
Machine Learning

• 1. Python.
• 2. C
• R Program
• Jupyter Notebook
• Tableau

• 1. Python.
• R Program
• Jupyter Notebook
• Tableau
• Keras

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