Sentiment Analysis with RNNs in Keras

О курсе

Build practical sentiment analysis skills using Recurrent Neural Networks (RNNs), Long Short-Term Memory (LSTM) networks, Keras, and Python. Designed for learners who want hands-on experience with deep learning for Natural Language Processing (NLP), this project-based course guides you through classifying IMDB movie reviews by sentiment in Google Colab. You’ll begin by exploring sentiment analysis fundamentals, setting up the Colab environment, and downloading the IMDB dataset. You’ll then prepare text sequences for RNN training through tokenization and padding. As you progress, you’ll learn the foundations of LSTM networks and construct, train, and evaluate both simple and complex LSTM models. You’ll also plot model results, predict movie review sentiments, and optimize RNN models to improve classification accuracy. What makes this course distinctive is its step-by-step, implementation-focused approach: each concept is connected directly to practical Python coding. By the end, you’ll be able to preprocess text data, design and assess LSTM-based sentiment analysis models, interpret results, and apply deep learning techniques to NLP tasks. Enroll to build an end-to-end sentiment analysis workflow and strengthen your applied RNN and Keras skills.

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