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Python map() and lambda() Use Cases and Examples

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 In Python, map() and lambda functions are often used together for functional programming. Here are some examples to illustrate how they work. Python map and lambda top use cases 1. Using map() with lambda The map() function applies a given function to all items in an iterable (like a list) and returns a map object (which can be converted to a list). Example: Doubling Numbers numbers = [ 1 , 2 , 3 , 4 , 5 ] doubled = list ( map ( lambda x: x * 2 , numbers)) print (doubled) # Output: [2, 4, 6, 8, 10] 2. Using map() to Convert Data Types Example: Converting Strings to Integers string_numbers = [ "1" , "2" , "3" , "4" , "5" ] integers = list ( map ( lambda x: int (x), string_numbers)) print (integers) # Output: [1, 2, 3, 4, 5] 3. Using map() with Multiple Iterables You can also use map() with more than one iterable. The lambda function can take multiple arguments. Example: Adding Two Lists Element-wise list1 = [ 1 , 2 , 3 ]

Industrial IoT what GE says to improve Productivity

GE is once a top company in Heavy Engineering. This is to say items related to Thermal Power plants, Turbines, and maintenance.

GE had always believed that since it knew the materials and the physics of its jet engines and medical scanners, no one could best it in understanding those machines.

GE Industrial Internet

 The aim is it should not share its data to third parties.
  1.    GE sets up its own IoT center.
  2.    GE is in IoT mood.
  3.    GE can improve operational efficiency by studying data from its machines like situated India and Russia. This is just an example.
Asset classification in analytics

 GE is Targetting for Predictive Maintenace

  • Improves industrial productivity
  • Based on criticality productivity will zoom if maintenance carried in-time.

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