/* Import required modules */ import sched import time /* setup the scheduler with our time settings */ s = sched.scheduler(time.time, time.sleep)
/* Create a function we want to run in the future. */ def print_time(): print("Executive Order 66")
/* Create a function for the delay */ def print_some_times(): /* Create a scheduled job that will run */ /* the function called 'print_time' */ /* after 10 seconds, and with priority 1. */ s.enter(10, 1, print_time) /* Run the scheduler */ s.run()
/* Run the function for the delay */ print_some_times()
Executive Order 66
Python Example for Beginners
Two Machine Learning Fields
There are two sides to machine learning:
- Practical Machine Learning:This is about querying databases, cleaning data, writing scripts to transform data and gluing algorithm and libraries together and writing custom code to squeeze reliable answers from data to satisfy difficult and ill defined questions. It’s the mess of reality.
- Theoretical Machine Learning: This is about math and abstraction and idealized scenarios and limits and beauty and informing what is possible. It is a whole lot neater and cleaner and removed from the mess of reality.
Data Science Resources: Data Science Recipes and Applied Machine Learning Recipes
Introduction to Applied Machine Learning & Data Science for Beginners, Business Analysts, Students, Researchers and Freelancers with Python & R Codes @ Western Australian Center for Applied Machine Learning & Data Science (WACAMLDS) !!!
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