Movie Review Sentiment Analysis Project Part-5 | Building Embedding and LSTM Model using Tensorflow

Welcome to Part 5 of the Movie Review Sentiment Analysis Project!
In this video of the Movie Review Sentiment Analysis Project series, we cover how to build a deep learning model for text sentiment classification using TensorFlow.

✨ What you’ll learn in this video:
🔹 How to create Word Embeddings in TensorFlow
🔹 Basics of LSTM (Long Short-Term Memory) RNNs for text data
🔹 Why do we use LSTM instead of CNN for NLP tasks
🔹 Step-by-step implementation of an LSTM RNN model in TensorFlow

🚀 By the end of this session, you’ll understand how to design an LSTM architecture for sentiment analysis.
👉 In the next video, we will train the model, monitor its performance, and evaluate results on movie reviews.

🔗 Previous Video (Text Vectorization in NLP Explained):
   • Movie Review Sentiment Analysis Project Pa...  

🔗 IMDB Dataset:
https://www.kaggle.com/datasets/laksh...

🔗 Project Resources:
https://drive.google.com/drive/folder...

🔗 Full Playlist:
   • Movie Review Sentiment Analysis Project fr...  

🔗 LSTM Blog:
https://colah.github.io/posts/2015-08...

🔗 RNN Stanford:
https://stanford.edu/~shervine/teachi...

🔗 Tensorflow Embedding Layer:
https://www.tensorflow.org/api_docs/p...


👍 Don’t forget to Like, 💬 Comment, and 🔔 Subscribe for more tutorials on NLP, TensorFlow, and Deep Learning projects.

#TensorFlow #LSTM #SentimentAnalysis #DeepLearning #NLP #MovieReviews