In the "Build with AI - Sentiment Analysis with BERT" session, we will explore the capabilities of BERT, a revolutionary transformer model, and its impact on natural language processing (NLP). BERT has transformed sentiment analysis by enabling more nuanced understanding of language, improving model accuracy, and capturing context with bidirectional learning. This event will guide participants through the process of implementing BERT for sentiment analysis, covering key concepts like tokenization, fine-tuning, and evaluating the model's performance.

Participants will learn to preprocess text data, configure BERT for sentiment analysis, and interpret results. Whether you’re a beginner in AI or have experience in NLP, this event offers valuable insights and hands-on learning to help you build sentiment analysis models for applications in social media analysis, customer feedback, and beyond.

Learning Objectives:

Understand the concept and importance of sentiment analysis in natural language processing.

Learn about BERT’s architecture, bidirectional encoding, and how it processes contextual information.

Gain hands-on experience in applying BERT to sentiment analysis tasks, including data preparation, fine-tuning, and evaluation.

Explore real-world applications of sentiment analysis in industries like social media, marketing, and customer service.

Key Takeaways:

Comprehensive understanding of BERT and its significance in NLP tasks.

Practical knowledge of implementing BERT for sentiment analysis using Python and popular libraries.

Insights into the application of sentiment analysis in real-world scenarios.

Experience in data preparation, model fine-tuning, and evaluation specific to sentiment analysis