🎬 In this video, I show how to build a complete sentiment analysis system using the IMDB 50K Movie Reviews Dataset. We use LSTM (Long Short-Term Memory) — a type of deep learning model — to detect if a movie review is positive or negative.
🔧 What I do in this video:
Install and import libraries 📦
Load and explore the IMDB dataset 📊
Clean the reviews using NLTK (remove stopwords, lowercase, etc.) 🧹
Tokenize and pad the reviews ✂️
Build and train an LSTM model using TensorFlow 🧠
Check the accuracy and plot results 📈
Save the trained model 💾
✅ This is perfect for beginners in NLP, deep learning, and Python.
📁 Dataset
🔗 IMDB 50K Dataset:
https://www.kaggle.com/datasets/lakshmi25npathi/imdb-dataset-of-50k-movie-reviews
📌 Tools Used:
Python 🐍
TensorFlow / Keras 🔧
NLTK (for text cleaning)
Google Colab
🧠 What You Will Learn:
How to preprocess text data for NLP
How to use LSTM for classification
How to build a complete deep learning pipeline
💬 If you have questions, ask in the comments!
👍 Like the video if you find it helpful
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