Sentiment analysis for restaurant reviews (nlp) #584

[ghousiya47]

Pull Request for ML-Crate 💡

Issue Title: Sentiment Analysis for Restaurant Reviews (NLP) #584

• Info about the related issue (Aim of the project) : To build a machine learning model for predicting the Sentiments of Customer based on their review on a Restaurant.
• Name: GHOUSIYA BEGUM
• GitHub ID: ghousiya47
• Idenitfy yourself: Student -Mentee JWOC'24

Closes: #584 that will be closed through this PR

Describe the add-ons or changes you've made 📃

Give a clear description of what have you added or modifications made

Type of change ☑️

What sort of change have you made:

• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Code style update (formatting, local variables)
• Breaking change (fix or feature that would cause existing functionality to not work as expected)
• This change requires a documentation update

How Has This Been Tested? ⚙️

I have tested my model by checking it's testing and training accuracy, i got highest testing accuracy of around 93% for training accuracy 97% for SVM Algorithm.

Checklist: ☑️

• My code follows the guidelines of this project.
• I have performed a self-review of my own code.
• I have commented my code, particularly wherever it was hard to understand.
• I have made corresponding changes to the documentation.
• My changes generate no new warnings.
• I have added things that prove my fix is effective or that my feature works.
• Any dependent changes have been merged and published in downstream modules.

[github-actions]

Our team will soon review your PR. Thanks @ghousiya47 :)

[ghousiya47]

@abhisheks008 please review my PR.

[abhisheks008]

Didn't find out any NLP models/methods in this project.
@ghousiya47 please take a look at this.

[ghousiya47]

Didn't find out any NLP models/methods in this project. @ghousiya47 please take a look at this.

@abhisheks008 sir i have used TF-IDF and CountVectorizer techniques, this are NLP methods. Using CountVectorizer I have represented each review as a bag of its words, ignoring grammar and word order but keeping track of word frequency.

[ghousiya47]

@abhisheks008 I have even used nltk package, to remove stopwords and punctuation, This is an NLP technique

[abhisheks008]

@abhisheks008 I have even used nltk package, to remove stopwords and punctuation, This is an NLP technique

Replied you in Discord.

[ghousiya47]

@abhisheks008 I have even used nltk package, to remove stopwords and punctuation, This is an NLP technique

Replied you in Discord.

@abhisheks008 Sir I have updated my README.md file kindly review it.

[abhisheks008]

Approved under JWOC 2024 @ghousiya47