I will build a custom nlp sentiment analysis web app using python and streamlit

M
muh_zafran
M
muh_zafran
Zafii ML

About this gig

Are you looking for a professional sentiment analysis tool that classifies text as positive, negative, or neutral in real time?


I will build you a fully deployed, interactive sentiment analysis web app using Python, NLP (NLTK / TextBlob / VADER), and Streamlit no coding required on your end. Whether you need to analyze customer reviews, social media posts, survey responses, or product feedback, I will deliver a clean, working solution.


What you will get:

A trained NLP model (VADER / TextBlob or custom ML classifier)

Interactive Streamlit web app with real-time predictions

Clean visualizations (sentiment scores, bar charts, word clouds)

Full Python source code with comments

Deployed live link (Streamlit Cloud), share it with anyone


I can work with:

Amazon / product reviews

Twitter / social media data

Custom CSV datasets you provide

Any English-language text data


Why choose me:

I am an AI student and ML developer with hands-on experience building and deploying real NLP applications. I have built sentiment analysis systems with 90%+ accuracy and deployed them live on Streamlit Cloud.


Message me before ordering if you have a custom dataset. I will confirm it is compatible.

Get to know Zafii ML

Zafii ML

From raw data to intelligent ML models, fast and accurate

  • FromPakistan
  • Member sinceDec 2025
  • Languages

    Urdu, English
ML Engineer | Arch Technologies Intern | 98.6% spam detection & 99.2% digit recognition accuracy. I build real, deployed ML web apps — not just notebooks. Live app: zafii-diabetes-prediction.streamlit.app Skills: Classification, Regression, NLP, Time Series Forecasting, Computer Vision, Data Analysis (Python, TensorFlow, Scikit-learn, Streamlit, Pandas) 11 internship projects. 14 certifications (Simplilearn, GDG, Anthropic, Arch Technologies, and excelerate, etc.). Clean code. On-time delivery. 100% satisfaction guaranteed. Message me — I respond within 1 hour.

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