Natural Language Processing - Probability Models in Python
Explore Probability Models and Markov Chains for NLP with Python Programming
Created by Lazy Programmer
Explore the essentials of Natural Language Processing with Python by working through probability models and Markov chains. You'll apply these concepts to practical tasks such as text classification, article spinning, and cipher decryption, gaining hands-on experience with real-world coding challenges.
Packt | Jun 2024 | 262 min
What You Will Learn
You will start by understanding the basics of Markov models and probability in NLP, then move on to building text classifiers and article spinners with Python. Practical coding exercises and real-world case studies help you apply each concept, ensuring you gain both theoretical knowledge and hands-on skills.
Key Features
- Build and optimize Markov models for text classification and analysis
- Develop automated content generation tools using N-gram techniques
- Apply genetic algorithms to decrypt ciphers and explore NLP in cybersecurity
Target Audience
Ideal for intermediate Python developers, data scientists, or machine learning enthusiasts who want to deepen their NLP expertise. If you have a basic understanding of Python and probability, you'll find the material accessible and rewarding. Perfect for those aiming to tackle advanced NLP tasks or explore applications in text analysis and cybersecurity.
