Computer Hardware Dataset Analysis

abhisheks008 commented 5 months ago

ML-Crate Repository (Proposing new issue)

:red_circle: Project Title : Computer Hardware Dataset Analysis :red_circle: Aim : The aim of this project is to analyze the computer hardware dataset given here. :red_circle: Dataset : https://www.kaggle.com/datasets/dilshaansandhu/general-computer-hardware-dataset :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 :

You need to create a separate folder named as the Project Title.
Inside that folder, there will be four main components.
- Images - To store the required images.
- Dataset - To store the dataset or, information/source about the dataset.
- Model - To store the machine learning model you've created using the dataset.
- requirements.txt - This file will contain the required packages/libraries to run the project in other machines.
Inside the Model folder, the README.md file must be filled up properly, with proper visualizations and conclusions.

:red_circle::yellow_circle: Points to Note :

The issues will be assigned on a first come first serve basis, 1 Issue == 1 PR.
"Issue Title" and "PR Title should be the same. Include issue number along with it.
Follow Contributing Guidelines & Code of Conduct before start Contributing.

:white_check_mark: To be Mentioned while taking the issue :

Full name :
GitHub Profile Link :
Participant ID (If not, then put NA) :
Approach for this Project :
What is your participant role? (Mention the Open Source Program name. Eg. HRSoC, GSSoC, GSOC etc.)

Happy Contributing 🚀

All the best. Enjoy your open source journey ahead. 😎

zul132 commented 5 months ago

@abhisheks008 I am willing to work on this issue under JWOC. Kindly assign it to me

abhisheks008 commented 5 months ago

Please share your approach as per the issue template. @zul132

zul132 commented 5 months ago

Full name : Fathima Zulaikha GitHub Profile Link : https://github.com/zul132 Participant ID (If not, then put NA) : NA Approach for this Project : For the analysis of the given Computer Hardware Dataset, I have planned to use Linear Regression, Decision Trees, K-Nearest Neighbors (KNN) and Random Forest to implement the models. After implementing the models, I will evaluate their performance using appropriate metrics and compare them to find the best-fitted algorithm for the computer hardware dataset.

What is your participant role? I am participating under JWOC

zul132 commented 5 months ago

Full name : Fathima Zulaikha GitHub Profile Link : https://github.com/zul132 Participant ID (If not, then put NA) : NA Approach for this Project : For the analysis of the given Computer Hardware Dataset, I have planned to use Linear Regression, Decision Trees, K-Nearest Neighbors (KNN) and Random Forest to implement the models. After implementing the models, I will evaluate their performance using appropriate metrics and compare them to find the best-fitted algorithm for the computer hardware dataset.

What is your participant role? I am participating under JWOC

@abhisheks008

abhisheks008 commented 5 months ago

Assigned @zul132

zul132 commented 5 months ago

@abhisheks008 My wifi modem got damaged recently due to which I’m unable to work the ML project for this issue. Even my mobile hotspot is not getting connected to my PC. Is it possible to unassign me as the number of days allowed for Medium level (2-3 days) has already passed. My apologies for any inconveniences caused.

abhisheks008 commented 5 months ago

Sure @zul132

professor1412 commented 5 months ago

Full name : Kanhaiya Yadav
GitHub Profile Link : https://github.com/professor1412
Participant ID  : NA
Approach for this Project :The algorithm I want to apply is Linear regression , Decision tree,KNN etc.
What is your participant role? 
JWoC

assingned me please.

abhisheks008 commented 5 months ago

Assigned @professor1412

abhisheks008 commented 5 months ago

Hi @professor1412 any update on this issue, otherwise @prakharsingh-74 is ready to take up this issue.

professor1412 commented 5 months ago

sorry for inconvenience I am unable to manage time for this . so assign it to @prakharsingh-74

abhisheks008 commented 5 months ago

Cool. Assigned to @prakharsingh-74 under JWOC 2024.

abhisheks008 commented 5 months ago

You can combine the datasets altogether to make a huge dataset, you can work on that too. It's better to work with all the datasets.

abhisheks008 commented 5 months ago

Then use at least 3-4 datasets for this project which you find the most useful one.

abhisheks008 commented 5 months ago

Sure @prakharsingh-74

shivansh-2003 commented 1 month ago

Can You Please Assign this issue under SSOC. 2024 Season 3 Shivansh Mahajan Github:- https://github.com/shivansh-2003 Participation ID:- NA I will do EDA of the data set by various statistical methods like IQR , Study Distribution OF Feature and Correlation Matrix. I would train the data in Various ML model to. arrive to the better Accuracy score. I would then feed the data for Feature engineering and then train it with different machine learning models KNN , Random forest , Decision Tree , SVM and Bossting Algorithms . I am well versed with Machine Learning you can check out my linkedin :-https://www.linkedin.com/in/shivansh-mahajan-13227824a/ and Git repository . can u assign me with this issue @abhisheks008 Participation Role:- SSOC Season 3

abhisheks008 commented 1 month ago

Contributions will start from June 1, 2024. Till then please have some patience.

DarkRaiderCB commented 2 weeks ago

Full name : Sanyog Mishra GitHub Profile Link : https://github.com/DarkRaiderCB Participant ID: NA Approach for this Project : Will perform EDA on dataset provided using techniques like Data cleaning, categorial analysis, finding any outliers, visualisation (correlation matrix, heat maps and more), summary stats., etc. Would utilise feature engineering and use ML algorithms like Linear Regression, Decision Tree, XGBoost, KNN, etc. and will find the best performing model. Will also try to make use of Tensorflow library. Tools to be used: Pandas, Numpy, Matplotlib, Scikit Learn, XGBoost, Tensorflow. Resume: https://drive.google.com/file/d/1sDVtq69GJd83t4H1-EOlvHEyQc2oat1k/view?usp=drive_link Participant Role: Contributor SSOC Season 3

abhisheks008 commented 2 weeks ago

Full name : Sanyog Mishra GitHub Profile Link : https://github.com/DarkRaiderCB Participant ID: NA Approach for this Project : Will perform EDA on dataset provided using techniques like Data cleaning, categorial analysis, finding any outliers, visualisation (correlation matrix, heat maps and more), summary stats., etc. Would utilise feature engineering and use ML algorithms like Linear Regression, Decision Tree, XGBoost, KNN, etc. and will find the best performing model. Will also try to make use of Tensorflow library. Tools to be used: Pandas, Numpy, Matplotlib, Scikit Learn, XGBoost, Tensorflow. Resume: https://drive.google.com/file/d/1sDVtq69GJd83t4H1-EOlvHEyQc2oat1k/view?usp=drive_link Participant Role: Contributor SSOC Season 3

Issue assigned to you @DarkRaiderCB

abhisheks008 / ML-Crate

Computer Hardware Dataset Analysis #503

ML-Crate Repository (Proposing new issue)

📍 Follow the Guidelines to Contribute in the Project :