Build an AI Sentiment Analysis App with Python & Streamlit (Full AI Project Hands-on Tutorial)

In this hands-on tutorial, we build a complete AI Sentiment Analysis Dashboard from scratch using Python! 🚀 Whether you are a beginner or a Data Scientist looking to deploy your first LLM app, this video guides you line-by-line. We use the Hugging Face Transformers library to detect positive, negative, and neutral sentiments in customer reviews and visualize the data using Streamlit. The best part? We do this WITHOUT needing any complex API keys or paid subscriptions. We finish by deploying the app live to the web using Hugging Face Spaces so you can share it with your friends or recruiters. 📂 **Download the Code & Dataset:** datase link: https://www.kaggle.com/datasets/kundanbedmutha/customer-sentiment-dataset/data model repo is here: https://huggingface.co/lxyuan/distilbert-base-multilingual-cased-sentiments-student 🧠 **Models & Libraries Used:** * Model: lxyuan/distilbert-base-multilingual-cased-sentiments-student * Library: Streamlit, Transformers, Pandas * Hosting: Hugging Face Spaces (Free Tier) ⏱️ **Timestamps:** 0:00 - Intro: What we are building 2:36 - Setting up VS Code & Libraries 5:56 - Coding for the App from Import of the libraries and modules 8:40 - Loading of the model and using for Sentiment Analysis 11:47 - Develop main app interface with tabs for single and multiple reviews 27:45 - Recap of entire steps 30:35 - Run the streamlit app and run the sentiment analysis 👨‍🏫 **About Me:** I am a Data Scientist at Nissan and an educator at Great Learning, teaching and mentoring Machine Learning and AI to students at top universities like MIT, JHU and UT Austin. I love making complex data concepts simple and actionable. 🔔 **Subscribe for more hands-on Data Science projects!** #Python #MachineLearning #Streamlit #HuggingFace #DataScience #NLP #PortfolioProject #AI #transformers #generativeai #genai #deeplearning #neuralnetworks #sentimentanalysis