Sentiment Analysis with RNNs and Keras

Natural language processing is a crucial field in modern technology, yet building your first text-classification model can feel overwhelming. This text-based course guides you step-by-step through the process of constructing a recurrent neural network to analyze textual sentiment. You will transition from understanding how computers process words to deploying a functional neural network that determines the emotional tone of written reviews. What you'll learn: Understand core natural language processing concepts and text preprocessing steps; Configure embedding layers to translate words into meaningful vectors; Practice padding sequences to ensure uniform input dimensions; Build a recurrent neural network architecture using Keras; Train and evaluate your model on real-world text data; Apply modern validation techniques to prevent model overfitting. The course begins with foundational concepts in NLP and text representation, then moves into data preparation, and concludes with hands-on network construction and evaluation. This course is designed for beginners who have a basic understanding of Python and want to enter the world of deep learning. Start building your first sentiment analysis model today.