02-17-2025, 02:05 AM
NLP in Python: Probability Models, Statistics, Text Analysis
Master Language Models, Hidden Markov Models, Bayesian Methods and Sentiment Analysis for Real-World Applications
New
Rating: 0.0 out of 5
(0 ratings)
1,064 students
6.5 hours on-demand video
Description
Unlock the power of Natural Language Processing (NLP) with this comprehensive, hands-on course that focuses on probability-based approaches using Python. Whether you're a data scientist, software engineer, or ML enthusiast, this course will transform you from a beginner to a confident NLP practitioner through practical, real-world projects and exercises.
Starting with fundamental text processing techniques, you'll progressively master advanced concepts like Hidden Markov Models, Probabilistic Context-Free Grammars, and Bayesian Methods. Unlike other courses that only scratch the surface, we dive deep into the probabilistic foundations that power modern NLP applications while keeping the content accessible and practical.
What sets this course apart is its project-based approach. You'll build:
A complete text preprocessing pipeline
Custom language models using N-grams
Part-of-speech taggers with Hidden Markov Models
Sentiment analysis systems for e-commerce reviews
Named Entity Recognition models using probabilistic approaches
Through carefully designed mini-projects in each section and a comprehensive capstone project, you'll gain hands-on experience with essential NLP libraries and frameworks. You'll learn to implement various probability models, from basic Naive Bayes classifiers to advanced topic modeling with Latent Dirichlet Allocation.
By the end of this course, you'll have a robust portfolio of NLP projects and the confidence to tackle real-world text analysis challenges. You'll understand not just how to use popular NLP tools, but also the probabilistic principles behind them, giving you the foundation to adapt to new developments in this rapidly evolving field.
Whether you're looking to enhance your career prospects in data science, improve your organization's text analysis capabilities, or simply understand the mathematics behind modern NLP systems, this course provides the perfect balance of theory and practical implementation
https://www.udemy.com/course/nlp-in-python-probability-models-statistics-text-analysis/?couponCode=ROSE25NOW
Enjoy!
Master Language Models, Hidden Markov Models, Bayesian Methods and Sentiment Analysis for Real-World Applications
New
Rating: 0.0 out of 5
(0 ratings)
1,064 students
6.5 hours on-demand video
Description
Unlock the power of Natural Language Processing (NLP) with this comprehensive, hands-on course that focuses on probability-based approaches using Python. Whether you're a data scientist, software engineer, or ML enthusiast, this course will transform you from a beginner to a confident NLP practitioner through practical, real-world projects and exercises.
Starting with fundamental text processing techniques, you'll progressively master advanced concepts like Hidden Markov Models, Probabilistic Context-Free Grammars, and Bayesian Methods. Unlike other courses that only scratch the surface, we dive deep into the probabilistic foundations that power modern NLP applications while keeping the content accessible and practical.
What sets this course apart is its project-based approach. You'll build:
A complete text preprocessing pipeline
Custom language models using N-grams
Part-of-speech taggers with Hidden Markov Models
Sentiment analysis systems for e-commerce reviews
Named Entity Recognition models using probabilistic approaches
Through carefully designed mini-projects in each section and a comprehensive capstone project, you'll gain hands-on experience with essential NLP libraries and frameworks. You'll learn to implement various probability models, from basic Naive Bayes classifiers to advanced topic modeling with Latent Dirichlet Allocation.
By the end of this course, you'll have a robust portfolio of NLP projects and the confidence to tackle real-world text analysis challenges. You'll understand not just how to use popular NLP tools, but also the probabilistic principles behind them, giving you the foundation to adapt to new developments in this rapidly evolving field.
Whether you're looking to enhance your career prospects in data science, improve your organization's text analysis capabilities, or simply understand the mathematics behind modern NLP systems, this course provides the perfect balance of theory and practical implementation
https://www.udemy.com/course/nlp-in-python-probability-models-statistics-text-analysis/?couponCode=ROSE25NOW
Enjoy!