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Machine Learning for Emotion Analysis in Python: Build AI-powered tools for analyzing emotion using natural language processing and machine learning - Allan Ramsay,Tariq Ahmad - cover
Machine Learning for Emotion Analysis in Python: Build AI-powered tools for analyzing emotion using natural language processing and machine learning - Allan Ramsay,Tariq Ahmad - cover
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Machine Learning for Emotion Analysis in Python: Build AI-powered tools for analyzing emotion using natural language processing and machine learning
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Machine Learning for Emotion Analysis in Python: Build AI-powered tools for analyzing emotion using natural language processing and machine learning - Allan Ramsay,Tariq Ahmad - cover
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Kickstart your emotion analysis journey with this step-by-step guide to data science success Key Features Discover the inner workings of the end-to-end emotional analysis workflow Explore the use of various ML models to derive meaningful insights from data Hone your craft by building and tweaking complex emotion analysis models with practical projects Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionArtificial intelligence and machine learning are the technologies of the future, and this is the perfect time to tap into their potential and add value to your business. Machine Learning for Emotion Analysis in Python helps you employ these cutting-edge technologies in your customer feedback system and in turn grow your business exponentially. With this book, you’ll take your foundational data science skills and grow them in the exciting realm of emotion analysis. By following a practical approach, you’ll turn customer feedback into meaningful insights assisting you in making smart and data-driven business decisions. The book will help you understand how to preprocess data, build a serviceable dataset, and ensure top-notch data quality. Once you’re set up for success, you’ll explore complex ML techniques, uncovering the concepts of deep neural networks, support vector machines, conditional probabilities, and more. Finally, you’ll acquire practical knowledge using in-depth use cases showing how the experimental results can be transformed into real-life examples and how emotion mining can help track short- and long-term changes in public opinion. By the end of this book, you’ll be well-equipped to use emotion mining and analysis to drive business decisions.What you will learn Distinguish between sentiment analysis and emotion analysis Master data preprocessing and ensure high-quality input Expand the use of data sources through data transformation Design models that employ cutting-edge deep learning techniques Discover how to tune your models’ hyperparameters Explore the use of naive Bayes, SVMs, DNNs, and transformers for advanced use cases Practice your newly acquired skills by working on real-world scenarios Who this book is forThis book is for data scientists and Python developers looking to gain insights into the customer feedback for their product, company, brand, governorship, and more. Basic knowledge of machine learning and Python programming is a must.
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Dettagli

2023
Paperback / softback
334 p.
Testo in English
235 x 191 mm
9781803240688

Conosci l'autore

Allan Ramsay

(Leadhills, Lanarkshire, 1686 - Edimburgo 1758) poeta scozzese. Tra i maggiori protagonisti della rinascita nazionale e culturale scozzese, nel 1712 fondò a Edimburgo un famoso circolo letterario, l’«Easy Club», modellato sullo «Spectator» di Addison. Diede vita alla prima biblioteca circolante inglese (1728) e al primo teatro stabile di Edimburgo (1736). La sua libera parafrasi (1716) dell’antico poema La chiesa di Cristo sul verde (Christis-Kirk on the green, attribuito a Giacomo I di Scozia) ebbe tale successo che in seguito curò altre edizioni di antiche ballate popolari scozzesi (che costituirono più tardi una delle principali fonti letterarie di poeti come Burns): Canti scozzesi (Scots songs, 1719), Il sempreverde (The evergreen, 1724), i tre volumi dello Zibaldone per il tè (The tea-table...

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