Natural Language Processing with TensorFlow

Text data is everywhere, from customer reviews to social media feeds, but extracting meaning from raw words requires specialized machine learning techniques. This course guides you through the fundamentals of processing human language using TensorFlow. You will transition from understanding basic text representation to building neural network models that can classify sentiment, predict sequences, and analyze linguistic patterns. What you'll learn: - Understand foundational NLP concepts, text tokenization, and vocabulary indexing. - Apply word embeddings to capture semantic meaning in low-dimensional vector spaces. - Build recurrent neural networks and LSTMs to model sequential text data. - Configure convolutional neural networks for text classification and sentiment analysis. - Explore modern transformer concepts and attention mechanisms within the TensorFlow ecosystem. - Practice preprocessing raw text datasets to prepare them for robust model training. The course begins with essential terminology, text cleaning, and basic preprocessing before moving into sequence modeling and advanced architectures. You will progress through written explanations and structured code snippets to build your conceptual and practical understanding. This program is designed for beginners eager to explore machine learning for text, with no prior NLP experience required. Start reading today to unlock the power of language modeling with TensorFlow.