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Natural Language Processing - Machine Learning Models in Python
Natural Language Processing - Machine Learning Models in Python

Natural Language Processing - Machine Learning Models in Python: Mastering Text Analytics: From Spam Detection to Topic Modeling

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Video Jun 2024 5hrs 11mins 1st Edition
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Can$139.99
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Video Jun 2024 5hrs 11mins 1st Edition
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Can$139.99
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Key benefits

  • Spam detection, sentiment analysis, text summarization, topic modeling, and latent semantic analysis.
  • Hands-on coding sessions in Python to apply theoretical knowledge.
  • In-depth exploration of model evaluation metrics and advanced algorithms.

Description

Embark on a journey through the world of text analytics with our expertly crafted course. Starting with an introduction and outline, you'll discover the foundational concepts and receive a special offer to get you started. The initial sections guide you through the setup process, ensuring you have all the resources and tips needed for success. Delve into the core of text analytics with dedicated sections on spam detection, sentiment analysis, text summarization, topic modeling, and latent semantic analysis. Each section begins with a problem description, followed by intuitive explanations of algorithms like Naive Bayes, logistic regression, and Latent Dirichlet Allocation. You'll engage with practical exercises designed to reinforce your understanding, and apply these techniques using Python in a hands-on manner. The course culminates with advanced topics and comprehensive summaries, ensuring you grasp both the theoretical and practical aspects of text analytics. By the end, you'll have a robust understanding of various NLP techniques and the confidence to apply them in real-world scenarios. This course is an essential resource for technical professionals looking to excel in the rapidly evolving field of natural language processing.

Who is this book for?

This course is ideal for data scientists, machine learning engineers, and software developers with a basic understanding of Python and machine learning concepts. Familiarity with statistics and linear algebra will be beneficial but not mandatory.

What you will learn

  • Develop spam detection models using Naive Bayes in Python.
  • Apply logistic regression for sentiment analysis of text data.
  • Implement text summarization techniques, including TextRank and vector-based methods.
  • Perform topic modeling with LDA and NMF in Python.
  • Understand and apply latent semantic analysis using SVD.
  • Evaluate and improve model performance using metrics like ROC, AUC, and F1 scores.

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Jun 21, 2024
Length: 5hrs 11mins
Edition : 1st
Language : English
ISBN-13 : 9781836205579
Category :
Languages :
Concepts :
Tools :

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Product Details

Publication date : Jun 21, 2024
Length: 5hrs 11mins
Edition : 1st
Language : English
ISBN-13 : 9781836205579
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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