Название: Build Your Own Neural Networks: Step-By-Step Explanation For Beginners
Автор: Kilho Shin
Издательство: Independently published
Год: 2024
Страниц: 210
Язык: английский
Формат: epub
Размер: 10.1 MB

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 (AI).

"Build Your Own Neural Networks: Step-By-Step Explanation For Beginners" is designed to demystify the complexities of neural networks for those who are new to the field of Deep Learning. This book is your comprehensive guide to understanding and implementing neural networks from the ground up, using the PyTorch framework. Each chapter is structured to provide hands-on experience with practical code examples, detailed step-by-step explanations, and engaging mini-projects that ensure a practical understanding of the concepts discussed. This approach not only enhances learning but also makes the journey fun and interactive. By avoiding complex jargon and focusing on clear, simple explanations, we ensure that you gain a solid foundation in neural networks without feeling overwhelmed.

To break down the abstract world of Neural Networks, we will start with one concrete tool- Python, amongst the most popular languages for Machine Learning and Deep Learning development. To best exploit Python’s various capabilities, an understanding of some fundamental concepts and functions is essential.

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 ideal for anyone who has a basic understanding of programming and a curiosity about Artificial Intelligence and Machine Learning. Whether you are a student, a hobbyist, or a professional looking to switch careers, this book will equip you with the knowledge you need to start building your own neural networks. It's especially useful for readers who prefer learning by doing and enjoy hands-on projects that reinforce learning. No prior experience with Deep Learning frameworks is required, as we start from the very basics and gradually progress to more complex topics.

Why You’ll Love This Book:

Easy 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.

Start your journey into neural networks today with "Build Your Own Neural Networks: Step-By-Step Explanation For Beginners" and unlock the secrets of AI.

Grab your copy now and begin building your own neural networks!








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