Natural Language Processing - Embeddings and Text Preprocessing in Python
Master text preprocessing and vector models in Python for powerful NLP applications
Created by Lazy Programmer
Explore the essentials of natural language processing in Python by mastering text preprocessing and vector models. Move from foundational techniques like tokenization and stemming to advanced skills such as TF-IDF and neural word embeddings. Gain practical coding experience to tackle real-world NLP challenges confidently.
Packt | Jun 2024 | 368 min
What You Will Learn
You will learn through a mix of clear explanations, hands-on coding demonstrations, and interactive exercises. Each topic builds on the last, so you can gradually develop your skills and apply them to practical NLP problems. By the end, you will be ready to use these techniques in your own projects.
Key Features
- Apply tokenization, stemming, and lemmatization to clean and prepare text data
- Build and evaluate vector models including Bag of Words and TF-IDF with Python
- Use neural word embeddings to enhance NLP applications beyond basic text analysis
Target Audience
Ideal for data scientists, machine learning engineers, and software developers who already know basic Python and want to deepen their NLP expertise. If you are looking to process and analyze text data more effectively or build smarter applications, this course will help you reach your goals.
