AWS: Chatbot
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 Step 1: from AWS Management Consol, search 'Lex'
 Step 2: click [Create a bot] -> choose [Create a blank bot]
         -> give a name -> choose [create a role with basic AWS permissions]
         -> No for COPPA -> Time out 5 (default) -> [Next]
         -> English [default] -> Mattew (for voice)
         -> 0.4 (default value for Intent classification confidence score threshold]
         -> click [Done]
 Step 3: From AWS click 'bots', we will find our generated bot
         -> Select 'intent' -> choose your generated intent by name
         -> give a name for [Intent name]
         -> add [uttrance]   Hi, Hello, Hey etc   
         -> [Closing response] add your response to 'Hi'
         -> add variations as well
         -> [save intent]
 Step 4: -> built and test it out
 Step 5: -> click 'Intents' -> click [Add an intent]
         -> [Add an empty intent]
         -> give a name, then click [Add]
         -> add uttrances and responses  
         -> [save intent]
 Step 6: add slots under 'intent' choose 'slot types]
         -> give a name -> for value choose 'single', double, triple 
         -> save slot type
 Step 7: Go back to intent -> [add slot]
         -> [add prompt] [add] -> [save intent]
         -> closing response
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AWS: Lambda function 
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 Step 1: Create an S3 budget
 Step 2: AWS Management Consol -> Lambda
         -> click [Create function]     [Note: blueprint will give you sample code]
         -> click [Author from scratch] 
         -> [a name]
         -> [run time drop-down list] choose 'Python 3.10'
         -> create function
         -> Permission
 Step 3:

https://www.youtube.com/watch?v=3Ar1ABlD_Vs

https://www.youtube.com/watch?v=EBSdyoO3goc&t=13s
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AWS: SageMaker
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 Step 1: AWS Management Consol -> SageMaker-> SageMaker Studio
          -> click [Create domain]
          -> [choose a role]    -> [submit]

         'Choose a VPC' dialog box that appears, select the "Default vpc" option.

 Step 2: [Launch App]-> Choose [Studio] instead of Canvas
         [note: wait for a few minutes]->click [SageMaker JumpStart]

 Step 3: ML Tasks -> Data Science??
         Click 'File' -> New Launcher-> Create a new notebook

         Type print("Hello World")

 Step 4: Create a new folder named 'Resources'
         click '+' on the left-top
         rename is as 'Resources' -> then click the up-arrow key to load data
          
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