This Natural Language Processing (NLP) Zero to Hero series is a structured learning path that takes learners from basic concepts to advanced deep learning applications in NLP. It starts with tokenization, where sentences are broken down into smaller units so machines can understand text data more effectively.
The course then moves into sequencing, which transforms text into numerical data that machine learning models can process. After that, learners explore sentiment analysis, where models are trained to understand emotions and opinions expressed in text.
As the series progresses, it introduces deep learning techniques such as Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM) networks. These models are essential for understanding sequences in language, such as sentences and context over time.
The final part of the course focuses on advanced applications like training AI models to generate text, including creative tasks such as poetry generation. This demonstrates how modern NLP systems can not only understand language but also generate human-like text.
By the end of this series, learners gain a strong understanding of how natural language processing evolves from simple text preprocessing to advanced generative AI systems.
