MACHINE LEARNING (2 Credits)
Learning Outcomes : On successful completion of this course, student will be able to: Explain the fundamental of machine learning concept; Interpret the distribution of dataset using regression metho...
Learning Outcomes : On successful completion of this course, student will be able to: Explain the fundamental of machine learning concept; Interpret the distribution of dataset using regression metho...
Learning Outcomes: On successful completion of this course, student will be able to: LO1 - explain fundamental machine learning concepts and differentiate between AI, Machine Learning, and Deep Learn...
Learning Outcomes: On successful completion of this course, student will be able to: Explain concepts and challenges of machine learning systems Demonstrate feature engineering techniques on ...
Learning Outcomes: On successful completion of this course, students will be able to: explain concepts and challenges of machine learning systems; demonstrate feature engineering techniques on th...
Learning Outcomes: On successful completion of this course, students will be able to: LO1 - Explain fundamental concepts of machine learning; LO2 - Demonstrate feature engineering techniques to get i...
Learning Outcomes: On successful completion of this course, student will be able to: Explain the fundamental of machine learning concept Interpret the distribution of dataset using regression...
Learning Outcomes: On successful completion of this course, students will be able to: Explain the fundamental concept of Machine Learning and its various techniques/algorithms; Describe the character...
Learning Outcomes: On successful completion of this course, student will be able to: LO1 - explain the fundamental of machine learning concept; LO2 - interpret the distribution of dataset using regre...
Learning Outcomes: On successful completion of this course, students will be able to: LO1 - define machine learning concepts, techniques and algorithms; LO2 - explain machine learning process for the...
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