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Item #:
3968852
Deep Learning with Python
86% of respondents would recommend this to a friend
Item #:
3968852
NZD 99
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What Stands Out
Comprehensive Guide
This edition provides a thorough introduction to deep learning concepts, making complex ideas accessible for beginners and experienced programmers interested in practical applications.
Hands-on Examples
Incorporates coding examples and projects that allow readers to implement deep learning algorithms, enhancing learning through practical experience and real-world applications.
Expert Insights
Authored by renowned experts, the book offers valuable insights into industry best practices, ensuring that readers are not only learning theory but also current trends and methodologies.
Product Details
| Publisher | Manning |
| Publication date | December 22, 2017 |
| Edition | First Edition |
| Language | English |
| Print length | 384 pages |
| ISBN-10 | 9781617294433 |
| ISBN-13 | 978-1617294433 |
| Item Weight | 1.42 pounds (640 grams) |
| Dimensions | 7.38 x 0.8 x 9.25 inches (18.7 x 2 x 23.5 cm) |
Who Should Buy?
-
Aspiring Data Scientists
Ideal for beginners seeking to understand deep learning concepts and applications using Python in practical scenarios.
-
Intermediate Programmers
Great for those who have programming experience and want to dive deeper into machine learning techniques.
-
Academic Researchers
Useful for scholars looking for a comprehensive introduction to deep learning concepts for academic purposes.
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Complete Beginners
Not suitable for individuals without any programming or mathematical background in machine learning or neural networks.
Product Description
Deep Learning with Python
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Intelligence & Semantics Editorial Review
Deep Learning with Python offers an engaging introduction to deep learning, crafted by Francois Chollet. The book uses Python code instead of complex mathematical equations, making it accessible for beginners and professionals alike. Many readers appreciated Chollet's clear explanations and structured approach, noting that it helps demystify the concepts within deep learning. The inclusion of practical implementation examples allows readers to quickly start building their own models, which is great for learning by doing. However, some critiques pointed out a lack of exercises and a somewhat superficial treatment of advanced concepts, leaving readers wanting more depth in certain areas. Overall, it's an excellent starting point for those new to AI, especially given its focus on using Keras for deep learning models.
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Pros
- Engaging writing style makes complex topics accessible
- Focus on Python code instead of heavy math
- Includes practical implementation examples
- Ideal for beginners with some programming experience
- Structured approach aids comprehension
Cons
- Could benefit from more in-depth exploration of advanced topics
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