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Machine Learning Fundamentals

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Machine Learning Fundamentals

 

Course Overview:

Machine Learning (ML) is the killer app for Big Data. Amazon Machine Learning brings the power of ML to a regular programmer and provides ML as a service. However, to use ML effectively, one needs to understand the models used.

Goals:

  • Provide a high-level introduction to data science and machine learning
  • Provide example of cutting-edge applications and breakthroughs
  • Motivate with the results of data science
  • Teach how to identify problems that can be solved with data science

Audience :

Anyone interested in data science

Duration :

1 day

Lab Environment

Demos will be provided.

 

Course Outline:

Data Science intro.

  • What is it and why is data science important?
    • How Data Science empowers management to take better decisions
    • How Data Science finds trends that lead to actions
    • How Data Science helps identify new opportunities
    • How Data Science helps identify the right target audience
  • How to identify what problems can be solved with Data Science and Machine Learning?
    • Data types, data formats, data cleaning
    • Enhancing data from additional sources
    • Building a quick prototype to assess the capabilities of a given Data Science solution
    • Training and verifying the model
    • Achieving the maximum possible prediction quality
  • How to communicate with people about data science
    • Data Science vocabulary
    • Supervised and unsupervised learning
    • Model quality
    • Data quality
    • Will getting more data help me achieve a better return on investment?
  • What security concepts should one think about before solving for a problem using DS
    • Data is your major asset
    • How to protect your data
    • Encryption in motion
    • Encryption in place
    • Best practices in security
  • Wrapping up
    • A practical plan of action
    • Learning pointers