Recently I built a small sentiment analysis project as part of my learning journey in Artificial Intelligence and Machine Learning.
The goal of this project was simple: create a model that can analyze text and predict whether the sentiment is positive or negative.
Why I Built This Project
While learning machine learning concepts, I realized that the best way to understand them is by building small practical projects. Sentiment analysis is a common beginner NLP project and a great way to understand how text data can be processed by machine learning models.
What the Project Does
The program takes a piece of text as input and predicts the sentiment.
Example:
Input:
"I love this product"
Output:
Positive sentiment
Technologies Used
Python
scikit-learn
Natural Language Processing (NLP)
Project Structure
train.py – trains the machine learning model
predict.py – predicts sentiment from text input
app.py – runs the application
vectorizer.pkl – saved text vectorizer
sentiment_model.pkl – trained model
What I Learned
This project helped me understand:
how text data is processed
how machine learning models are trained
how predictions are made from new input data
GitHub Repository
You can check out the project here:
https://github.com/alenkurian-ml/sentimentanalysisbasic
Final Thoughts
This is a small step in my journey of learning Artificial Intelligence and Machine Learning. I plan to continue building more projects and improving my understanding of AI concepts.
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