Current Trends Prelim Q1

A TYPE OF ML WHERE IT TRAINS THE MACHINE USING DATA WHICH IS “LABELLED”

• SUPERVISED

• UNSUPERVISED

• SEMI-SUPERVISED

• REINFORCEMENT

A TYPE OF ML WHERE IT TRAINS THE MACHINE USING THE COMBINATION OF “LABELLED” DATA & “UNLABELLED” DATA

• SUPERVISED

• UNSUPERVISED

• SEMI-SUPERVISED

• REINFORCEMENT

A BRANCH OF ARTIFICIAL INTELLIGENCE CONCERN THE CONSTRUCTION AND STUDY OF SYSTEMS THAT CAN LEARN FROM DATA.

• ROBOTICS

• MACHINE LEARNING

• NEURAL NETWORK

• DEEP LEARNING

A TYPE OF MACHINE LEARNING IN WHICH THE USERS DO NOT NEED TO SUPERVISE THE MODEL AND USES “UNLABELLED” DATA.

IT IS THE RELATIONSHIP BETWEEN FEATURES AND LABELS.

STEPS OF ML THAT IS A METHOD OF ASSESSING THE CORRECTNESS OF MODELS ON TEST DATA.

• CHOOSE A MODEL

• TRAIN THE MODEL

• EVALUATE A MODEL

• PARAMETER TUNING

GIVE THE FOUR TYPES OF MACHINE LEARNING(ALGORITHMS)(4)

IT REFERS TO THE FIELDS USED AS INPUT. ALSO REFERS AS A SINGLE COLUMN OF DATA IN YOUR INPUT SET.

TYPE OF ML WHERE MACHINE LEARNING MODELS ARE TRAINED TO MAKE A SERIES OF DEISIONS BASED ON THE REWARDS AND FEEDBACKS RECEIVED FOR THERI ACTIONS.

• SEPERVISED

• UNSUPERVISED

• SEMI-SUPERVISED

• REINFORCEMENT

TRUE/FALSE: IN TRADITIONAL PROGRAMMING, DATA AND PROGRAM ARE PUT INTO COMPUTER TO PRODUCE OUTPUT.

• TRUE

• FALSE

• MAYBE

• IT NOT EXIST!