Build Your Own Neural Networks Step-By - Step Explanation For Beginners

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Free Download Build Your Own Neural Networks: Step-By-Step Explanation For Beginners by Kilho Shin
English | June 23, 2024 | ISBN: N/A | ASIN: B0D7VHY973 | 210 pages | EPUB | 9.23 Mb
Build Your Own Neural Networks: Step-By-Step Explanation For Beginners

Are you curious about how neural networks work and want to build your own from scratch? "Build Your Own Neural Networks" is the perfect guide for beginners looking to dive into the fascinating world of artificial intelligence.
What's Inside?
This book takes you on a journey from the basics to advanced topics, making complex concepts easy to understand with clear explanations and practical examples.Introduction to Neural Networks: Learn what neural networks are, how they work, and explore their real-world applications and challenges.Setup and Installation: Get step-by-step instructions on setting up your programming environment, including using Jupyter Notebooks and Python basics.Numpy for Neural Networks: Master the essential Numpy library for handling data and performing array operations critical for neural network building.Building Blocks of Neural Networks: Understand neurons, activation functions, forward and backpropagation, and how to train a neural network.Designing Your First Neural Network: Design, train, and evaluate your first neural network with hands-on guidance.Advanced Neural Network Design: Explore advanced topics like regularization, dropout, and hyperparameter tuning to optimize your models.Convolutional Neural Networks (CNNs): Dive into CNNs for image processing with detailed explanations of convolutional, pooling, and fully connected layers.Recurrent Neural Networks (RNNs): Learn about RNNs and LSTMs for sequence data and time-series analysis.Deploying a Neural Network Model: Discover how to save, load, and deploy your models effectively in real-world applications.Keeping Up With Neural Network Trends: Stay updated with the latest research, resources, and ethical considerations in AI.Who This Book Is For
This book is for anyone with a keen interest in neural networks, whether you're a student, professional, or hobbyist. No prior experience in AI or neural networks is required.
Why You'll Love This BookEasy to Understand: Written in simple, friendly language with a focus on clarity and practical learning.Step-by-Step Guidance: Each chapter builds on the previous one, ensuring you gain a solid understanding as you progress.Hands-On Examples: Practice what you learn with hands-on examples and exercises.



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