You will get Emotion Detection using Machine Learning | TF-IDF & SVM
Project details
This project focuses on building an Emotion Detection system using Machine Learning and Natural Language Processing techniques. I started by cleaning and preparing the dataset using Pandas and DataFrames, including removing duplicate and unnecessary data. Then, I used TF-IDF to convert text data into numerical features suitable for machine learning models.
I trained and tested multiple classification models, including Logistic Regression, Multinomial Naive Bayes, and Support Vector Classifier (SVC). To understand which model performed best, I evaluated and compared their results using Accuracy, Precision, F1-score, and Classification Reports.
The project demonstrates a complete machine learning workflow, from data preprocessing and feature extraction to model training, evaluation, and performance comparison.
I trained and tested multiple classification models, including Logistic Regression, Multinomial Naive Bayes, and Support Vector Classifier (SVC). To understand which model performed best, I evaluated and compared their results using Accuracy, Precision, F1-score, and Classification Reports.
The project demonstrates a complete machine learning workflow, from data preprocessing and feature extraction to model training, evaluation, and performance comparison.
Machine Learning Tools
NumPy, pandas, Python, Python Scikit-Learn, scikit-learnWhat's included $25
These options are included with the project scope.
$25
- Delivery Time 5 days
- Number of Revisions 2
- Number of Model Variations 1
- Number of Scenarios 1
- Number of Graphs/Charts 0
- Model Validation/Testing
- Source Code
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Fast 3 Days Delivery
+$30About Arouba
i want to get money to buy everything i need ,the first car
Jordan customs, Jordan - 6:40 am local time
i want to get rid of boredom and depression by doing something useful that changs my life by earning money..
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Emotion Detection Machine Learning Project
Machine learning project for emotion detection using TF-IDF, multiple models, and performance evaluation.