Open mariam7084 opened 4 months ago
Full name : Niharika Khanna GitHub Profile Link : nkhanna94 Participant ID (If not, then put NA) : NA Approach for this Project : To analyze fictional e-commerce sales data, I'll start with a detailed EDA to understand data patterns and relationships. After cleaning and preprocessing the data, I'll build predictive models using 3-4 different algorithms and compare these models to determine the best fit based on accuracy scores. What is your participant role? SSOC S3
One issue at a time @nkhanna94
Hey I completed the previous issue, please assign this to me now.
Hey I completed the previous issue, please assign this to me now.
Please complete your previous issue.
Name: Aryan Yadav github: https://github.com/aryan0931 Participant id:NA Approach for this project: I will perform Exploratory Data Analysis (EDA) on the provided dataset using techniques such as data cleaning, categorical analysis, outlier detection, and visualization (including correlation matrices, heat maps, and more). This process will involve generating summary statistics and conducting feature engineering to prepare the data for machine learning. For the machine learning analysis, I will utilize algorithms like Linear Regression, Decision Trees, XGBoost, and K-Nearest Neighbors (KNN) to identify the best-performing model. The tools and libraries used for this analysis will include Pandas, NumPy, Matplotlib, Scikit-Learn, and XGBoost. Participant role: SSOC S3
Implement 5-6 models for this project. Assigned @aryan0931
ML-Crate Repository (Proposing new issue)
:red_circle: Project Title : Fictional E - Commerce Sales Analysis :red_circle: Aim : Peform EDA :red_circle: Dataset : https://www.kaggle.com/datasets/hassaneskikri/fictional-e-commerce-sales-data :red_circle: Approach : Try to use 3-4 algorithms to implement the models and compare all the algorithms to find out the best fitted algorithm for the model by checking the accuracy scores. Also do not forget to do a exploratory data analysis before creating any model.
📍 Follow the Guidelines to Contribute in the Project :
requirements.txt
- This file will contain the required packages/libraries to run the project in other machines.Model
folder, theREADME.md
file must be filled up properly, with proper visualizations and conclusions.:red_circle::yellow_circle: Points to Note :
:white_check_mark: To be Mentioned while taking the issue :
Happy Contributing 🚀
All the best. Enjoy your open source journey ahead. 😎