Difference between revisions of "Spring 2025: Software Engineering Lab"

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# '''Sandeep Kumar Sharma (25047)'''
 
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# '''Shivam Soni (250xx)'''
 
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# ⁠Kashif (250xx)
 
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# Akash Pathak (250xx)
 
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# ⁠Priyanshu Sachan (250xx)
 
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Revision as of 13:12, 15 December 2024

Instructions

  • Please be on time to avoid the Attendance Penalty.
  • Please put your mobile phone in the Silent Mode.
  • Each lab assignment needs to be submitted in the Google Classroom for evaluation(will be notified in the GC lab-wise, submit before the deadline).
  • Turn off(shut down) your assigned computer and arrange the chair before you leave the lab.

Guidelines

Lab 0: Getting Started ( week of 05th & 12th August 2024 )

Q. NO. Program Practical No. Remarks
1 https://www.cse.msu.edu/~ptan/dmbook/tutorials/tutorial1/tutorial1.html Practice Set No. 1 Introduction to Python
2 https://www.cse.msu.edu/~ptan/dmbook/tutorials/tutorial2/tutorial2.html Practice Set No. 2 Introduction to Numpy and Pandas
3 https://www.cse.msu.edu/~ptan/dmbook/tutorials/tutorial3/tutorial3.html Practice Set No. 3 Data Exploration

Lab 1: ( week of 19th & 26th August 2024 )

Q. NO. Program Practical No. Remarks
1 Apply data cleaning techniques on any dataset (e.g. Chronic Kidney Disease dataset from UCI repository). Techniques may include handling missing values, outliers and inconsistent values. Also, a set of validation rules may be specified for the particular dataset and validation checks performed. Practical No. 1 Dataset: kidneyDisease.csv

Download from Kaggle: Chronic KIdney Disease dataset
Tutorial: Tutorial on Handling Missing values

Lab 2: ( week of 2nd & 9th September 2024 )

Q. NO. Program Practical No. Remarks
1 Apply data pre-processing techniques such as standardization/normalization, transformation, aggregation, discretization/binarization, sampling etc. on any dataset Practical No. 2 Dataset: rain.csv

Download from data.gov.in: Rainfall in India

Lab 3: ( week of 16th, 23rd & 30thSeptember 2024 )

Q. NO. Program Practical No. Remarks
1 Writing/Review of Chapter 1, Chapter 3, and Chapter 4 of Project Report Project Work

Lab 4: ( week of 7th October 2024 )

Q. NO. Program Practical No. Remarks
1 Apply simple K-means algorithm for clustering any dataset. Compare the performance of clusters by varying the algorithm parameters. For a given set of parameters, plot a line graph depicting MSE obtained after each iteration. Practical No. 3 Dataset: Mall_Customers.csv

Download from data from kaggle: Mall Customer Segmentation Data

Projects

Team No. Project Title Team Members Outcomes/Remarks
1 Title 1
  1. Name (RollNo.)
  2. Name (RollNo.)
  3. Name (RollNo.)
  4. Name (RollNo.)
  • Report:
  • Project Presentation:
2 Title 2
  1. Name (RollNo.)
  2. Name (RollNo.)
  3. Name (RollNo.)
  4. Name (RollNo.)
  • Report:
  • Project Presentation:
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