Chicago Bike Share Data Analysis

[abhisheks008]

ML-Crate Repository (Proposing new issue)

:red_circle: Project Title : Chicago Bike Share Data Analysis :red_circle: Aim : Analyse the dataset given using different parameters. :red_circle: Dataset : https://www.kaggle.com/datasets/avneeshsingh19/chicago-bike-share-data-2021 :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.

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📍 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.

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: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.
• This issue is only for 'SWOC' and 'JWOC' contributors of 'ML-Crate' project.

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: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.)

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Happy Contributing 🚀

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

[Suyogsm]

please assign it to me i am willing to solve it

[abhisheks008]

Please follow the issue template and provide all the details accordingly. @Suyogsm

[Suyogsm]

Full Name: Suyog Mayekar GitHub Link: https://github.com/Suyogsm Participant ID: NA Approach For this project: I will try to use 3-4 algorithms to implement the models and compare all the algorithms to find out the best fitting algorithm for the model by checking the accuracy scores. Also, I will perform an exploratory data analysis before creating any model.

please assign the topic to me I am willing to solve it

[abhisheks008]

Issue assigned to you @Suyogsm

[abhisheks008]

Issue has been un-assigned from you due to inactivity. @Suyogsm

[susanyeldo]

Full name : Susanna P Yeldo GitHub Profile Link : https://github.com/susanyeldo Participant ID (If not, then put NA) : NA Approach for this Project : Data visualization using Pandas and mathplotlib What is your participant role? kWOC

[abhisheks008]

Issue assigned to you @susanyeldo

[abhisheks008]

Unassigned. ML-Crate is going to be part of DWOC from Jan, 15, all the unfinished issues will be taken by the contributors of DWOC.

[Avdhesh-Varshney]

@abhisheks008 i would like to work on this issue. Could you please assign it to me?

Full name : Avdhesh Varshney GitHub Profile Link : https://github.com/Avdhesh-Varshney Participant ID (If not, then put NA) : Approach for this Project :

• Analysing the dataset.
• EDA processing.
• Filtering the dataset so that which can easily fit into any type of the model.
• Applying the different type of the algorithms like, random forest, linear regression, xgboost, knn classifier, svm classifier, etc.
• Summarizing all the algorithms at the end of the notebook.

What is your participant role? (Mention the Open Source Program name. Eg. HRSoC, GSSoC, GSOC etc.) KWOC

[pawaspy]

@abhisheks008 Can you assign me this? I have registered in JwOc. Full name :Pawas Pandey GitHub Profile Link :github.com/pawaspy Participant ID (If not, then put NA) :NA Approach for this Project : I have different method to perform on this. I will preprocess the data and use different graphs for the analysis. What is your participant role? (Mention the Open Source Program name. Eg. HRSoC, GSSoC, GSOC etc.) : JWOc

[abhisheks008]

Let the program start officially. The issues will be assigned thereafter. @pawaspy

[pawaspy]

Can you assign me this task? Full name :Pawas Pandey GitHub Profile Link :github.com/pawaspy Participant ID (If not, then put NA) :NA Approach for this Project : I have different method to perform on this. I will preprocess the data and use different graphs for the analysis. What is your participant role? (Mention the Open Source Program name. Eg. HRSoC, GSSoC, GSOC etc.) : IWoC

[abhisheks008]

This issue is part of JWOC.

[Mudassir-A]

Full name : Mohd Mudassir Ansari GitHub Profile Link : Mudassir-A Participant ID (If not, then put NA) : NA Approach for this Project : Will use Python Programming to analyse the dataset and gain insights about when to launch and what type of bikes to be launched as per the users' analysis. What is your participant role? : JWOC

[Lycons-rage]

I would like to work on this issue

• Full name : Chinmaya Tewari
• GitHub Profile Link : https://github.com/Lycons-rage
• Participant ID (If not, then put NA) : NA
• Approach for this Project : I would like to implement classification algorithms like Random Forest Classifier, Logistic Regression, SVC, AdaBoost, GBMs, to classify preferred ride_type based on distances and also classify the rider as member and casual. Before that, I will be doing the EDA and implementing the required preprocessing on the dataset
• What is your participant role? (Mention the Open Source Program name. Eg. HRSoC, GSSoC, GSOC etc.) SSoC 2024

[abhisheks008]

Need to implement 7-8 models for this problem statement.

Assigned @Lycons-rage

[Lycons-rage]

For sure @abhisheks008 Should I communicate here for any further assist, if required??

[abhisheks008]

For sure @abhisheks008 Should I communicate here for any further assist, if required??

You can drop a text in Discord channel for ML-Crate in SSOC server for further communications.