Begin your journey of NLP and deep learning with our complete tutorial, “Mastering Natural Language Processing (NLP) with Deep Learning,” which aims to make you understand the usage of text data. First of all, you will be introduced to NLP as a field and its cornerstone, text data, and how it is preprocessed for different tasks. These are facts and basic information that can come in handy when dealing with such a relatively new and dynamic sector.
In the next part, we’ll discuss how neural networks are used in NLP, and we’ll start with the sequence models and then look at the recurrent neural networks (RNNs). You will realize how these imposing models can be employed in textual analysis, giving you the ability and capacity to develop additional splendid NLP work. There is no doubt that these concepts may not be very easy to understand. Otherwise, we would not be categorizing things at such depth. However, to make it easier for you, we will be presenting them in lessons this way, and even if you have a shallow learning knowledge of deep learning, you will be in a position to understand.
Last of all, the attendees will be introduced to the practical application of transformer models such as BERT and GPT. These are regarded as the current generation of NLP models and are applied in numerous practical tasks. In ‘Mastering Natural Language Processing (NLP) with Deep Learning,’ you can understand and apply these models to solve various language processing problems and gain the knowledge to build new AI solutions.
Mastering Natural Language Processing (NLP) with Deep Learning Table of Contents:
- Introduction to Natural Language Processing (NLP) (1 min)
- NLP Essentials: Exploring Text Data (20 mins)
- NLP Architectures, Sequence Models, and Transformers (20 mins)
Who is this course for?
- Beginners in NLP and Deep Learning: Users interested in science, natural language processing, and practical deep learning are searching for a brief on the two fields.
- Data Enthusiasts: The intended audience will be those who love data analysis and are interested in applying deep learning to text data.
- Aspiring AI Professionals: This book is ideal for students and professionals in artificial intelligence and machine learning who are desirous of establishing a career in NLP.
- Developers and Engineers: Software developers and engineers who want to learn NLP and deep learning to enhance computer science.
