Experiment Repository Creation Request for Introductory Data Science Lab

[AmritaValueCS-22]

Repository Creation Request

Use this to get your experiment repository created or updated on GitHub under Virtual Labs organization.

1. Coordinating Institute: Amrita Vishwa Vidyapeetham

2. Approver’s Name: Vipin Pavithran, Arjun T U

3. Approved Proposal:[Proposal for Data Science (2).pdf]

   (https://github.com/user-attachments/files/17326916/Proposal.for.Data.Science.2.pdf)

4. Hosted url:

5. Primary GitHub Handle Details:

   Name: VALUE Virtual Labs

   GitHub Handle:@AmritaValueCS-22

   Email id: virtual_labs@am.amrita.edu

6. Secondary GitHub Handle Details:

   Name:

   GitHub Handle:

   Email id:

[ravikiran2020]

@AmritaValueCS-22 Please find the links for Introductory Data Science Lab experiments and populate the repositories with sources of the experiments as detailed in Step 4 of the migration document

1. Introduction to NumPy, Arrays and Array Operations - https://github.com/virtual-labs/exp-numpy-arrays-au
2. Introduction to Pandas - https://github.com/virtual-labs/exp-pandas-intro-au
3. Data Visualisation using Matplotlib - https://github.com/virtual-labs/exp-data-visualisation-au
4. Exploratory Data Analysis (EDA) - https://github.com/virtual-labs/exp-eda-au
5. Data Preprocessing - https://github.com/virtual-labs/exp-data-preprocessing-au
6. Evaluation Metrics, Overfitting/Underfitting and Train/Test Splits - https://github.com/virtual-labs/exp-eval-metrics-au
7. Movie Review Sentiment Analysis using Naïve Bayes - https://github.com/virtual-labs/exp-movie-sentiment-au
8. Predicting Student Performance Based on Study Hours using Linear Regression - https://github.com/virtual-labs/exp-student-performance-lr-au
9. Predicting Student Performance Based on Study Hours: A Comparison of Linear, Lasso, and Ridge Regression - https://github.com/virtual-labs/exp-student-performance-comp-au
10. Predicting Credit Card Fraud using Support Vector Machine - https://github.com/virtual-labs/exp-credit-fraud-svm-au
11. Predicting Customer Churn in a Telecommunications Company using Decision Tree and Random Forest - https://github.com/virtual-labs/exp-customer-churn-au
12. Clustering wines using K-Means - https://github.com/virtual-labs/exp-clustering-wines-au
13. Model Validation and Performance Evaluation - https://github.com/virtual-labs/exp-model-validation-au
14. Building a Handwritten digit classifier using Neural Networks - https://github.com/virtual-labs/exp-handwritten-classifier-au
15. Data Ethics and Bias in Machine Learning - https://github.com/virtual-labs/exp-data-ethics-bias-au