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Item #:
254358188
Machine Learning and Deep Learning With Python: Use Python Jupyter to Implement Mathematical Concepts, Machine Learning , (Paperback)
Item #:
254358188
XPF 6385
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Product Details
- This book is a comprehensive guide to understanding and implementing cutting-edge machine learning and deep learning techniques using Python programming language. Written with both beginners and experienced developers in mind, this book provides a thorough overview of the foundations of machine learning and deep learning, including mathematical fundamentals, optimization algorithms, and neural networks.Starting with the basics of Python programming, this book gradually builds up to more advanced topics, such as artificial neural networks, convolutional neural networks, and generative adversarial networks. Each chapter is filled with clear explanations, practical examples, and step-by-step tutorials that allow readers to gain a deep understanding of the underlying principles of machine learning and deep learning.Throughout the book, readers will also learn how to use popular Python libraries and packages, including numpy, pandas, scikit-learn, TensorFlow, and Keras, to build and train powerful machine learning and deep learning models for a variety of real-world applications, such as regression and classification, K-means, support vector machines, and recommender systems.Whether you are a seasoned data scientist or a beginner looking to enter the world of machine learning, this book is the ultimate resource for mastering these cutting-edge technologies and taking your skills to the next level. High-school level of mathematical knowledge and all levels (including entry-level) of programming skills are good to start, all Python codes are available at Github.com.
| Book format | Paperback |
| Fiction/nonfiction | Non-Fiction |
| Genre | Computing & Internet |
| Publication date | February, 2023 |
| Pages | 376 |
| Subgenre | Artificial Intelligence |
| Series title | No Series |
| Edition | 1 |
| Publisher | James Chen |
| Original languages | English |
| Language | English |
| Edu focus | Technology |
| Educational level | High School |
| Is collectible | N |
| Recording time | 0 min |
| Retail packaging | Single Piece |
| Assembled product dimensions (l x w x h) | 6.00 x 0.78 x 9.00 in (15.2 x 2 x 22.9 cm) |
| Assembled product weight | 1.11 lb (500 grams) |
| Bisac subject heading | Computers |
Product Description
Machine Learning and Deep Learning With Python: Use Python Jupyter to Implement Mathematical Concepts, Machine Learning , (Paperback)
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Customer Questions & Answers
-
Question:
Do I need prior knowledge in programming to understand this book?
Answer: No, the book is designed for all levels, including beginners. -
Question:
What Python libraries will I learn to use?
Answer: You will learn to use libraries like numpy, pandas, scikit-learn, TensorFlow, and Keras. -
Question:
Is there a specific mathematical background required?
Answer: A high-school level of mathematical knowledge is sufficient to start.
James Chen All Books Editorial Review
Machine Learning and Deep Learning With Python: Use Python Jupyter to Implement Mathematical Concepts, Machine Learning is a comprehensive guide that merges theoretical concepts with practical implementation in a sleek paperback format. With 376 pages of insightful content focused on artificial intelligence, this book is designed for non-fiction readers who wish to delve into the world of computing and internet technologies. Published in February 2023, it is tailored for high school educational levels, making it accessible for students eager to learn about machine learning, particularly through Python programming. Readers have appreciated the structured approach to mathematical concepts and practical applications of machine learning, making it a suitable choice for beginners in the field.
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Pros
- Comprehensive guide to machine learning concepts
- Accessible for high school students
- Focused on practical Python implementation
- Covers essential AI subgenres
- Well-structured content for easy understanding
Cons
- Might be too basic for advanced learners
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XPF 6385
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Features & Benefits
- Comprehensive guide to machine learning and deep learning using Python.
- Suitable for both beginners and experienced developers.
- Covers mathematical fundamentals, optimization algorithms, and neural networks.
- Includes practical examples and step-by-step tutorials.
- Focuses on popular Python libraries like numpy, pandas, and TensorFlow.
- Ideal for mastering advanced technologies in real-world applications.
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