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Ensemble Machine Learning Cookbook

You're reading from  Ensemble Machine Learning Cookbook

Product type Book
Published in Jan 2019
Publisher Packt
ISBN-13 9781789136609
Pages 336 pages
Edition 1st Edition
Languages
Concepts
Authors (2):
Dipayan Sarkar Dipayan Sarkar
Profile icon Dipayan Sarkar
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Dipayan Sarkar holds a Masters in Economics and comes with 17+ years of experience. Dipayan has won international challenges in predictive modeling and takes a keen interest in the mathematics behind machine learning techniques. Before opting to become an independent consultant and a mentor in the data science and machine learning space with various organizations and educational institutions, he had served in the capacity of a senior data scientist with Fortune 500 companies in the US and Europe. He is currently associated with Great Lakes Institute of Management as a visiting faculty (Analytics) and BML Munjal University as an adjunct faculty (Analytics and Machine Learning). He has co-authored a book on "Ensemble Machine Learning with Python" with PACKT Publishing.
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Vijayalakshmi Natarajan Vijayalakshmi Natarajan
Profile icon Vijayalakshmi Natarajan
LinkedIn
Vijayalakshmi Natarajan holds an ME in Computer Science, comes with 4 years of industry experience. She is a data science enthusiast and is a passionate trainer in the field of data science & data visualization. She takes keen interests in deep diving into Machine Learning techniques. Her specialization includes machine learning techniques in the field of image processing.
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Table of Contents (14) Chapters close

Preface 1. Get Closer to Your Data 2. Getting Started with Ensemble Machine Learning 3. Resampling Methods 4. Statistical and Machine Learning Algorithms 5. Bag the Models with Bagging 6. When in Doubt, Use Random Forests 7. Boosting Model Performance with Boosting 8. Blend It with Stacking 9. Homogeneous Ensembles Using Keras 10. Heterogeneous Ensemble Classifiers Using H2O 11. Heterogeneous Ensemble for Text Classification Using NLP 12. Homogenous Ensemble for Multiclass Classification Using Keras 13. Other Books You May Enjoy

Sentiment analysis of movie reviews using an ensemble model

Sentiment analysis is another widely studied research area in natural language processing (NLP). It's a popular task performed on reviews to determine the sentiments of comments provided by reviewers. In this example, we'll focus on analyzing movie review data from the Internet Movie Database (IMDb) and classifying it according to whether it is positive or negative.

We have movie reviews in .txt files that are separated into two folders: negative and positive. There are 1,000 positive reviews and 1,000 negative reviews. These files can be retrieved from GitHub.

We have divided this case study into two parts:

  • The first part is to prepare the dataset. We'll read the review files that are provided in the .txt format, append them, label them as positive or negative based on which folder they have been put...
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Authors (2)

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Profile icon Dipayan Sarkar
LinkedIn
Dipayan Sarkar holds a Masters in Economics and comes with 17+ years of experience. Dipayan has won international challenges in predictive modeling and takes a keen interest in the mathematics behind machine learning techniques. Before opting to become an independent consultant and a mentor in the data science and machine learning space with various organizations and educational institutions, he had served in the capacity of a senior data scientist with Fortune 500 companies in the US and Europe. He is currently associated with Great Lakes Institute of Management as a visiting faculty (Analytics) and BML Munjal University as an adjunct faculty (Analytics and Machine Learning). He has co-authored a book on "Ensemble Machine Learning with Python" with PACKT Publishing.
Read more
See other products by Dipayan Sarkar
Profile icon Vijayalakshmi Natarajan
LinkedIn
Vijayalakshmi Natarajan holds an ME in Computer Science, comes with 4 years of industry experience. She is a data science enthusiast and is a passionate trainer in the field of data science & data visualization. She takes keen interests in deep diving into Machine Learning techniques. Her specialization includes machine learning techniques in the field of image processing.
Read more
See other products by Vijayalakshmi Natarajan
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