This Repository contains the lab Programs for On-Going Data Science and Analytics Lab (CSL DC205) Fall 2024

The following are the list of programs with their Jupyter-Notebook and Lecture notes (Will be updated each week)

Program	Jupyter Notebook	Lecture Notes
Q1. Write a Program to Explore various Data Manipulation Functions provided by Pandas and Visualize the Data Using Seaborn	Pandas Library Functions & Visualization Notebook	Currently Under Development
Q2. To predict if a person will purchase a product on a specific combination of Day, Discount and Free delivery using Naïve Bayesian Classifier.	Naive Bayes Classifer Notebook	Naive Bayes Classifier Lecture Notes
Q3. Predict Employee Salary based on Year of Experience using Linear Regression.	Linear Regression Notebook	Currently Under Development
Q4. Predict if a person will buy an SUV based on their Age and Estimated Salary using Logistic Regression.	Logistic Regression Notebook	Currently Under Development
Q5. Does Kyphosis exist after surgery using Decision Tree?	Decision Tree Notebook	Currently Under Development
Q6. Write a Program to Demonstrate Random Forest Algorithm	Random Forest Notebook	Currently Under Development
Q7. Predict if a person will buy a SUV based on Age and Estimated Salary using KNN?	KNN Notebook	Currently Under Development
Q8. Features Extraction from Text using Word Vectorization for Text Semantics?	1. Feature Extraction and Evalutaion Notebook Using SST2 Dataset 2. Feature Extraction and Evalutaion Notebook Using Basic Example	Currently Under Development
Q9. Sentiment Analysis from online news website using simple natural language processing.	Sentiement Analysis Notebook	Currently Under Development
Q10. Use of KmeansClustering algorithm for classifying persons into 5 categories according to their salary.	K-Means Clustering Notebook	Currently Under Development
Q11. Write a program for demonstrating (Support Vector Machine Classifier) SVM algorithm.	SVM Notebook	Currently Under Development

Environment Setup Guide

This guide provides instructions on how to recreate the development environment for this project using Conda or pip. You can set up the environment using either a YAML file or a requirements text file.

Note

Here in the lab while coding the notebooks we have used conda as a package manager and miniconda instead of anaconda as distribution because it has less number of pre installed packages and we can install packages as per our requirement. Miniconda_3 Installation Guide

Table of Contents

• Using required-env-packages-list.yml
• Using required-packages-list.txt
• Using pip

Using required-env-packages-list.yml

To create a Conda environment from a YAML file, follow these steps:

1. Open your terminal (Anaconda Prompt or command line).

2. Navigate to your project directory where the required-env-packages-list.yml file is located:

   cd path/to/your/project  

3. Create the environment by running the following command:

   conda env create -f required-env-packages-list.yml

4. Activate the environment with:

   conda activate <environment-name>

   Replace with the name specified in the YAML file.

Using required-packages-list.txt

To create a Conda environment from a text file, follow these steps:

1. Open your terminal (Anaconda Prompt or command line).

2. Navigate to your project directory where the required-packages-list.txt file is located:

   cd path/to/your/project

3. Create a new environment (replace with your desired name):

   conda create --name <environment-name> --file required-packages-list.txt

4. Activate the environment with:

   conda activate <environment-name>

Using pip

If you prefer to use pip to create a virtual environment, follow these steps:

1. Open your terminal.

2. Navigate to your project directory where the required-packages-list.txt file is located:

   cd path/to/your/project

3. Create a virtual environment (replace with your desired name):

   python -m venv <env-name>

4. Activate the virtual environment:

   1. On Windows:

      • In PowerShell :

      <env-name>\Scripts\Activate.ps1

      • In cmd :

      <env-name>\Scripts\activate.bat

   2. On macOS/Linux:

      source <env-name>/bin/activate

5. Install the required packages using:

   pip install -r required-packages-list.txt

Note

• Ensure you have Conda or Python installed on your system.
• If you encounter any issues while creating the environment, check that all packages listed in the files are available in your Conda channels or PyPI.
• It is recommended to regularly update your environment files as you add new packages to ensure reproducibility for other users.
• By following these instructions, you will be able to set up the development environment required for this project effortlessly. If you have any questions or need further assistance, feel free to open an issue in this repository.

Contributing

🤝 Feel free to open an issue in this repository if you encounter any issues with any of the notebook code and also if you want to add more programs to the repository then feel free to generate a pull request to this repository. Whole Community will appreciate your feedback and contributions. Thank you

License

This project is licensed under the MIT License. See the LICENSE file for details.