Advantages and disadvantages of ML .PPTX

Advance

1. MACHINE LEARNING TECHNOLOGY .

2. MACHINE LEARING TECHNOLOGY

3. THERE ARE 4 TYPES OF MACHINE LEARNING TECHNOLOGYS: SUPERVISED UNSUPERVISED SEMI- SUPERVISED REIN FORCE MENT LEARING

4. SUPERVISED : It is a subcategory of machine learning and artificial intelligence. UNSUPERVISED: machine learning is efficient in pattern finding. . 2) machine learning work is automated and does not require human intervation. SEMI- SUPERVISED : It is a combination of supervised and unsupervised learning. . 2) It uses a small amount of labelled data and a large amount of unlabelled data. 4) REIN- FORCE MENT: A subset of ML that allows an AL driven system ( sometimes referred to as an agent).

5. EXAMPLES OF MACHINE LEARNING TECHNOLOGY ▶ 1) FACIAL RECOGNITION. ▶ 2) CREDIT CARD FRAUD DETECTION. ▶ 3)RECOMMENTATION SYSTEMS. ▶ 4) LOAN APPLICATION APPRROVALS .

6. APPLICATION of MACHINE LEARNING TECHNOLOGY

7. Advantages and disadvantages of machine learning technology . . . . . ▶ ADVANTAGES: MACHINE LEARNING is efficient in pattern finding MACHINE LEARNING is automated and does not require human intervention MACHINE LEARNING algorithms are even evolving. wide application MACHINES allows us to do many things quicker or with less effort cost reduction

8. ▶ ▶ . ▶ . cost reduction Improved accuracy Data dependency. ▶ ▶ ▶ DISADVANTAGES : 1)It is a pretty time consuming to fix the mistakes in codes and programs ▶ . ▶ . ▶ . ▶ . only some people can memorize ( or) even write the code it is platform Independent language expensive to buy , maintain and repair The collection and use of this data raise privacy and security concerns.

9. ▶ . . . . MOUNIKA KOSURU Reg no: 23cse 182 Roll no : 24 D- section