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Programming Neural Networks with Python: Your Practical Guide to Building Smart AI Systems with Machine Learning and Deep Learning (Rheinwerk
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HKD 626
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Ensure you’re on the cutting edge of AI with this practical guide to programming neural networks and building smart AI systems.
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- Neural networks are at the heart of AI—so ensure you’re on the cutting edge with this guide! For true beginners, get a crash course in Python and the mathematical concepts you’ll need to understand and create neural networks. Or jump right into programming your first neural network, from implementing the scikit-learn library to using the perceptron learning algorithm. Learn how to train your neural network, measure errors, make use of transfer learning, implementing the CRISP-DM model, and more. Whether you’re interested in machine learning, gen AI, LLMs, deep learning, or all of the above, this is the AI book you need!Your practical introduction to programming neural networksDevelop and train simple and multi-layer networks with PythonLearn about algorithms, activation functions, transformers, and moreThe BasicsLearn about neural networks from the ground up! Understand how neural networks work and what their basic elements are, from algorithms and activation functions to transformers. Includes a primer on mathematics and Python for beginners!Putting Theory into PracticeDevelop different types of neural networks: simple ones, multi-layer ones, and even deep neural networks. Walk through diverse practical examples, from image classification to large language models (LLMs).Letting the Machines LearnTrain your newly created (or modified!) neural network. Get expert tips on skillfully using training data, selecting the right tools, increasing the hit rates of your models, and avoiding pitfalls.
| Publisher | Rheinwerk Computing |
| Publication date | May 28, 2025 |
| Edition | New |
| Language | English |
| Print length | 457 pages |
| ISBN-10 | 1493226967 |
| ISBN-13 | 978-1493226962 |
| Item Weight | 1.62 pounds (730 grams) |
| Dimensions | 1.25 x 7 x 10 inches (3.2 x 17.8 x 25.4 cm) |
Who Should Buy?
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Aspiring Data Scientists
Ideal for beginners eager to understand neural networks and implement AI solutions using Python programming.
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Academic Students
Great resource for university students in computer science or related fields, supplementing coursework in AI and machine learning.
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Software Developers
Beneficial for developers looking to expand their skill set with practical applications of machine learning and deep learning.
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Absolute Beginners
Not suitable for those with no programming background or basic understanding of Python before diving into neural networks.
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優點
- Clear and practical examples
- Well-structured content
- Covers deep learning comprehensively
- Great for beginners and experts
- Includes useful exercises
缺點
- Some topics may be advanced for new users.
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特色和優勢
- Practical introduction to programming neural networks with Python.
- Comprehensive coverage from beginner concepts to advanced techniques.
- Hands-on approach with diverse practical examples including image classification and large language models.
- Learn to develop and train both simple and multi-layer networks.
- Focus on essential algorithms, activation functions, and model optimization strategies.
- Perfect for anyone interested in machine learning, deep learning, and AI technology.
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