Natural Language Processing – Probability Models in Python

Natural Language Processing – Probability Models in Python
MP4 | Video: AVC 1280×720 | Audio: AAC 44KHz 2ch | Duration: 5H 11M | 1.04 GB

Text summarization is thoroughly explored with sections on vector-based methods and TextRank, from basic to advanced levels. Practical Python sessions ensure learners can implement these techniques. The course culminates with topic modeling, introducing LDA and NMF methods, complemented by Python coding exercises. A deep dive into Latent Semantic Analysis and applying SVD in NLP wraps up the curriculum, ensuring a well-rounded expertise in NLP.
What you will learn

Identify and implement spam detection algorithms
Conduct sentiment analysis using logistic regression
Apply advanced techniques like TextRank for summarization
Understand and implement topic modeling with LDA and NMF
Utilize Latent Semantic Analysis in Python projects