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Item #:
83622385
Step by Step Tutorial IMAGE CLASSIFICATION Using Scikit-Learn, Keras, And TensorFlow with PYTHON GUI
98% of respondents would recommend this to a friend
Item #:
83622385
MGA 190799
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Implement deep learning-based image classification using TensorFlow, Keras, and Scikit-Learn to unlock the potential of machine learning in real-world applications.
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What Stands Out
Comprehensive Guide
This tutorial offers in-depth coverage of image classification using popular libraries, ensuring a well-rounded understanding for beginners and experts alike.
Practical Examples
Step-by-step instructions and real-world examples enhance learning, making complex concepts approachable for readers seeking hands-on experience.
Python GUI Integration
Teaches integration of GUI with machine learning models, enabling users to create interactive applications, enhancing usability and appeal for projects and presentations.
Product Details
| Publisher | Independently published |
| Publication date | June 3, 2021 |
| Language | English |
| Print length | 210 pages |
| ISBN-13 | 979-8514388905 |
| Item Weight | 1.36 pounds (620 grams) |
| Dimensions | 8.5 x 0.48 x 11 inches (21.6 x 1.2 x 27.9 cm) |
Who Should Buy?
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Beginners in AI
Ideal for those starting in artificial intelligence and need guided instructions for image classification.
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Data Science Students
Great for students learning data science concepts who require practical applications of image classification.
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Python Developers
Useful for Python developers aiming to integrate machine learning into their projects using Scikit-Learn and TensorFlow.
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Advanced Practitioners
Not suitable for experienced users who seek in-depth theoretical knowledge rather than a tutorial approach.
Product Description
Step by Step Tutorial IMAGE CLASSIFICATION Using Scikit-Learn, Keras, And TensorFlow with PYTHON GUI
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Customer Questions & Answers
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Question:
What prior knowledge do I need to use this book?
Answer: Basic understanding of Python and machine learning concepts is recommended. -
Question:
Are there any coding examples in the book?
Answer: Yes, the book includes practical coding examples for each topic. -
Question:
Can I follow along without a cloud environment?
Answer: Yes, all examples can be executed locally using Python and the specified libraries.
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MGA 190799
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Features & Benefits
- Comprehensive tutorials on deep learning image classification.
- Covers multiple datasets, including monkey species and rock-paper-scissors.
- Utilizes popular libraries: TensorFlow, Keras, Scikit-Learn, OpenCV, Pandas, NumPy.
- Step-by-step guidance from dataset preparation to model predictions.
- Learn to evaluate model performance using accuracy and other metrics.
- Ideal for developers and data scientists eager to enhance their skills.
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