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Item #:
91909029
Text Processing And Sentiment Analysis Using Machine Learning And Deep Learning With Python Gui
Item #:
91909029
GMD 3529
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This project provided a comprehensive overview of sentiment analysis using state-of-the-art machine learning models.
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What Stands Out
User-Friendly Interface
The Python GUI ensures an intuitive user experience, making complex text processing and sentiment analysis accessible for users with varying levels of expertise, from beginners to advanced practitioners.
Advanced Algorithms
Utilizes cutting-edge machine learning and deep learning techniques, providing robust and accurate sentiment analysis that outperforms traditional methods, effectively addressing complex text data challenges.
Comprehensive Tutorials
Includes detailed, step-by-step tutorials that guide users through the implementation of text processing techniques, enhancing learning and practical application, making it valuable for educators and learners alike.
Product Details
| Publisher | Independently published |
| Publication date | March 12, 2022 |
| Language | English |
| Print length | 333 pages |
| ISBN-13 | 979-8431335075 |
| Item Weight | 2.11 pounds (960 grams) |
| Dimensions | 8.5 x 0.75 x 11 inches (21.6 x 1.9 x 27.9 cm) |
Who Should Buy?
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Data Scientists
Ideal for data scientists who need to analyze text data and derive insights using advanced machine learning techniques.
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Business Analysts
Useful for business analysts looking to assess customer sentiments to inform marketing strategies and improve customer satisfaction.
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Developers Learning ML
Great for developers who want to learn about machine learning and deep learning frameworks in a practical, hands-on environment.
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Absolute Beginners
Not suitable for absolute beginners with no background in programming or machine learning concepts, as it may overwhelm them.
Product Description
Text Processing And Sentiment Analysis Using Machine Learning And Deep Learning With Python Gui
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Customer Questions & Answers
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Question:
What machine learning models are covered in this book?
Answer: The book covers XGBoost, LightGBM, and LSTM for sentiment analysis. -
Question:
Is prior knowledge of Python required?
Answer: Basic Python knowledge is recommended, but the book provides detailed code explanations. -
Question:
Can the models be reused for future analyses?
Answer: Yes, the implementation allows for the loading of pre-trained models and preprocessed data.
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GMD 3529
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Features & Benefits
- Explore sentiment analysis with machine learning and deep learning models.
- Includes implementations for XGBoost, LightGBM, and LSTM using Python GUI.
- Learn to preprocess, build, train, and evaluate models on Twitter data.
- User-friendly features include model selection and visualization of results.
- Save time and effort by using pre-trained models and preprocessing data.
- Gain insights into key processes in natural language processing.
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