IMDB Review Analysis

[abhisheks008]

ML-Crate Repository (Proposing new issue)

:red_circle: Project Title : IMDB Review Analysis :red_circle: Aim : Perform Sentiment analysis on the data to see the statistics of what type of movie do users like. Sentiment analysis is the process of analysing the textual data and identifying the emotion of the user, Positive or Negative. :red_circle: Dataset : http://ai.stanford.edu/~amaas/data/sentiment/ :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.

Hello, ML-Crate contributors, this issue is only for the contribution purposes and allocated only to the participants of SWOC 2.0 Open Source Program.

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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.
• A Demo Project has been created to guide you about the whole structure of presenting the Project in this repository. Here's the link of the Demo Project - https://github.com/abhisheks008/ML-Crate/tree/main/Project-Demo-Folder

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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' 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 :
• Approach for this Project :
• Are you a participant of SWOC 2.0?
  • [ ] YES
  • [ ] No

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Happy Contributing 🚀

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

[yagyesh-bobde]

I want to work on this!

Full name : Yagyesh Bobde GitHub Profile Link : https://github.com/yagyesh-bobde Participant ID : 1131 Approach for this Project : First do an EDA then find which models are best for email spam classification Are you a participant of SWOC 2.0? YES

[abhisheks008]

Issue assigned @yagyesh-bobde

[abhisheks008]

@yagyesh-bobde It's been 27 days. What's the update here. Reply ASAP.

[krishna-NIT]

@abhisheks008 Can I start over this, I am interested

Full name : Shrikrushna Bhagwat GitHub Profile Link : https://github.com/krishna-NIT Participant ID : 930 Approach for this Project : EDA First and then some good plotting and finally presentation with conclusions Are you a participant of SWOC 2.0? YES

[abhisheks008]

Yeah you can work on it @krishna-NIT

[abhisheks008]

What's the update here @krishna-NIT

[krishna-NIT]

I did one analysis but I am not satisfied with it, will be completing it in 2 days at a max

[abhisheks008]

Okay complete that. Because the program is going to end in 25 days, hurry up! @krishna-NIT

[abhisheks008]

What's the update here @krishna-NIT. You've asked for 2 days max, now what's the status here?