Search results: 259
ITL
Data Analytics Lab Using R
- Teacher: DR SEEMA MAITREY [CSE]
- Teacher: Latika Sharma [CSIT]
- Teacher: Mr. Deep Kumar [CSIT]
Machine learning (ML) is a type of artificial intelligence (AI) that allows software applications to become more accurate at predicting outcomes without being explicitly programmed to do so. Machine learning algorithms use historical data as input to predict new output values.
Recommendation engines are a common use case for machine learning. Other popular uses include fraud detection, spam filtering, malware threat detection, business process automation (BPA) and predictive maintenance.
Why is machine learning important?
Machine learning is important because it gives enterprises a view of trends in customer behavior and business operational patterns, as well as supports the development of new products. Many of today's leading companies, such as Facebook, Google and Uber, make machine learning a central part of their operations. Machine learning has become a significant competitive differentiator for many companies.
- Teacher: Dr. Pratibha Singh [CSE AI&ML]
- Teacher: Dr. Gaurav Srivastav [CSE(AI)]
- Teacher: Dr. Shelly Gupta Gupta
- Teacher: Rashika Bangroo [CSIT]
- Teacher: Sonia Deshmukh [CSIT]
- Teacher: Dr. Sudhir Kumar Sharma [CSIT]
- Teacher: Dr. Sudhir Kumar Sharma [CSIT]
- Teacher: MR ANKUR BHARDWAJ [CSE]
- Teacher: Mr Gaurav Parashar [CSE]
- Teacher: MR HRIDAY KUMAR GUPTA [CSE]
- Teacher: Mr. UMANG RASTOGI [CSE]
- Teacher: Dr. Sushil Kumar [CSE]
- Teacher: Mr. Saurav Chandra [CSE]
Mechanical Engineering Department
B. Tech, VIth Semester
Make-Up Examination, (2020-21) Even Semester
(NDT) (KME 061)
1. Attempt all the questions
2. The question paper consist of 50 Questions
3. The duration of question paper is 90 minutes
4. The correct question will have a weightage of +2 marks
5. wrong answer has the weightage of 0 mark
6. Unattempted question fetches zero marks
The objective of this course is to develop the ability to apply the concepts, tools and techniques
of economics in analysing and interpreting business decisions.
- To understand the basic concepts of Marketing Analytics
- To study various tools to have marketing insights in various marketing areas through empirical data
- To interpret the marketing data for effective marketing decision making
- To draw inferences from data in order to answer descriptive, predictive, and prescriptive questions relevant to marketing managers