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Natural Language Processing - Probability Models in Python
Natural Language Processing - Probability Models in Python

Natural Language Processing - Probability Models in Python: Unlock the power of Python in NLP: From Spam Detection to Text Summarization and Topic Modeling

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Mex$2256.99
Video Jun 2024 5hrs 11mins 1st Edition
Video
Mex$2256.99
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Free Trial
Arrow left icon
Profile Icon Lazy Programmer
Arrow right icon
Mex$2256.99
Video Jun 2024 5hrs 11mins 1st Edition
Video
Mex$2256.99
Subscription
Free Trial
Video
Mex$2256.99
Subscription
Free Trial

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Key benefits

  • Comprehensive introduction to NLP techniques using Python
  • Detailed walkthroughs of spam detection, sentiment analysis, and text summarization
  • Advanced methods like TextRank and Latent Dirichlet Allocation (LDA)

Description

Beginning with an introduction and course outline, students are offered a special offer to kickstart their learning journey in this course. Initial sections guide you through the setup process and provide the necessary code resources. The course emphasizes strategies for success, ensuring learners are well-prepared from the start. The course delves into spam detection, beginning with a problem description and intuition behind Naive Bayes. Participants engage in exercises and learn to address class imbalance while evaluating models using ROC, AUC, and F1 scores. Practical implementation in Python solidifies understanding. Following this, the course transitions to sentiment analysis, covering problem description, logistic regression, and training. Exercises and Python-based projects enable learners to apply concepts effectively. 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.

Who is this book for?

This course is designed for technical professionals, data scientists, and developers with a basic understanding of Python programming and machine learning concepts. Familiarity with basic statistical methods is recommended but not required.

What you will learn

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

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Jun 24, 2024
Length: 5hrs 11mins
Edition : 1st
Language : English
ISBN-13 : 9781836201854
Category :
Languages :
Concepts :
Tools :

What do you get with a video?

Product feature icon Download this video in MP4 format
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Product feature icon DRM FREE - Read whenever, wherever and however you want
OR
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Product Details

Publication date : Jun 24, 2024
Length: 5hrs 11mins
Edition : 1st
Language : English
ISBN-13 : 9781836201854
Category :
Languages :
Concepts :
Tools :

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Table of Contents

7 Chapters
Welcome Chevron down icon Chevron up icon
Getting Set Up Chevron down icon Chevron up icon
Spam Detection Chevron down icon Chevron up icon
Sentiment Analysis Chevron down icon Chevron up icon
Text Summarization Chevron down icon Chevron up icon
Topic Modeling Chevron down icon Chevron up icon
Latent Semantic Analysis (Latent Semantic Indexing) Chevron down icon Chevron up icon
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