Application of probability and statistics in machine learning MK


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employee_1 = {‘name’: ‘david’, ‘dept’: ‘ops’, ‘post’: ‘NOC’, ‘salary’: 12000, ‘id’: 113}
employee_2 = {‘name’: ‘brain’, ‘dept’: ‘auto’, ‘post’: ‘DBA’, ‘salary’: 13000, ‘id’: 115}
employee_3 = {‘name’: ‘chris’, ‘dept’: ‘search’, ‘post’: ‘PJM’, ‘salary’: 20000, ‘id’: 150}
employees = [employee_1, employee_2, employee_3]
for employee in employees:

employee['salary'] = employee['salary'] + 1000

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Nested list in dictionary

favorite_thing = {‘foods’: ‘cheese’, ‘drinks’: [‘milk’, ‘juice’, ‘whisky’]}
for drink in favorite_thing[‘drinks’]:

print("I love " + drink)


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Dictionary nested list

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favorite_language = {‘brain’: [‘python’], ‘chris’: [‘c’, ‘ruby’], ‘david’: [‘power shell’], ‘tina’: [‘shell’, ‘go’, ‘c++’]}
for name, languages in favorite_language.items():

print("\n" + name.title() + " like programing language: ")
for language in languages:

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