Description:

This course will teach you how to build powerful Multi Class Text Classification models using Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) networks. You will learn the theory behind RNN and LSTM, preprocess text data, build and train RNN and LSTM models for multi-class text classification tasks, and evaluate model performance. By the end of this course, you will be able to apply these advanced deep learning techniques to solve real-world text classification problems.

Key Highlights:

• Understand RNN and LSTM networks
• Preprocess text data for classification
• Build multi-class text classification models
• Evaluate model performance

What you will learn:

• Understand RNN and LSTM
  Learn the theory and architecture of Recurrent Neural Networks and Long Short-Term Memory networks.
• Preprocess Text Data
  Explore text preprocessing techniques including tokenization, stop-word removal, and vectorization.
• Build Classification Models
  Implement RNN and LSTM models for multi-class text classification tasks.
• Evaluate Model Performance
  Assess the performance of your models using metrics like accuracy, precision, and recall.