Sentiment Analysis with LSTMs and BERT focuses on building advanced NLP models to detect and classify emotions and opinions from text data. It enables organizations to analyze customer feedback, social media content, and reviews to understand sentiment patterns. This training explains how LSTM-based models capture sequential context in text, while BERT leverages transformer architecture for deep contextual understanding. It also covers preprocessing techniques, word embeddings, attention mechanisms, model fine-tuning, and evaluation metrics. You will learn how businesses use these models to improve customer experience, brand monitoring, and decision-making. The course also highlights best practices for building accurate and scalable sentiment analysis systems.
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