Автор: Vishаl Rаjрut
Издательство: Orange Education Pvt Ltd, AVA
Год: November 2023
Формат: epub (true)
Размер: 10.1 MB
Master Neural Networks for Building Modern AI Systems.
This book is a practical guide to the world of Artificial Intelligence (AI), unraveling the math and principles behind applications like Google Maps and Amazon.
The book starts with an introduction to Python and AI, demystifies complex AI math, teaches you to implement AI concepts, and explores high-level AI libraries.
Throughout the chapters, readers are engaged with the book through practice exercises and supplementary learnings. The book then gradually moves to Neural Networks with Python before diving into constructing ANN models and real-world AI applications. It accommodates various learning styles, letting readers focus on hands-on implementation or mathematical understanding.
This book isn't just about using AI tools; it's a compass in the world of AI resources, empowering readers to modify and create tools for complex AI systems. It ensures a journey of exploration, experimentation, and proficiency in AI, equipping readers with the skills needed to excel in the AI industry.
Is this book for me?
Since you're here, the answer is a resounding yes! So, let’s dive deeper into the details. Whether you're intrigued by the fundamentals of Python, eager to construct neural networks from the ground up, curious about the mathematical optimizations that drive these unique AI systems, or keen on building an entire AI pipeline, this book has got you covered on all fronts.
Our comprehensive guide aims to demystify the core concepts of Neural Networks, providing you with a deep understanding while ensuring an engaging learning experience. We believe in learning by doing, so this book incorporates hands-on sessions to actively involve and captivate our readers. Prepare to embark on a captivating journey that will empower you with the knowledge and skills needed to comprehend the inner workings of AI. With a focus on practicality and a firm foundation in Python, this book will equip you with the tools necessary to build, optimize, and deploy neural networks and bring your AI projects to life. Join us on this enlightening adventure as we unravel the intricacies of Neural Networks and ignite your passion for AI. So, get ready to explore, experiment, and excel!
This book perfectly fits software engineers looking to dive into AI. It provides ample opportunities to explore and practice AI concepts while leveraging the Python programming language. You'll gain valuable insights and practical skills from algorithms to real-life product implementation. Discover how to create AI-powered solutions and unleash your potential in the exciting field of AI.
Machine Learning Enthusiasts and Engineers
This book will advance your understanding if you're already well-versed in AI and have a solid foundation. It offers an opportunity to delve deeper into AI concepts, providing hands-on training that allows you to build projects from scratch. By engaging in practical exercises, you'll gain a more comprehensive understanding of AI and sharpen your skills. Prepare to expand your knowledge and expertise as you embark on a hands-on exploration and learning journey.
This book caters to AI researchers by offering clear explanations of mathematical concepts used in AI algorithms. It also guides writing production-level code, addressing a common challenge researchers face. Expand your understanding of AI and enhance your ability to apply it effectively in real-life scenarios with this valuable resource.
What is the book’s goal?
• Introduce our readers to the basics of Python and how to use it for AI purposes.
• Help readers understand complex mathematical concepts by giving them an easy breakdown of mathematical equations, which can later be applied to understand the complex mathematics behind modern AI systems.
• Enable our readers to write mathematical concepts behind AI algorithms in a code format by implementing things from scratch without using high-level libraries such as TensorFlow or PyTorch.
How is this book structured?
This book aims to comprehensively understand Artificial Neural Networks (ANN) and guide readers in building ANN models using Python. In addition, it explores the practical applications of ANN in various industries and academic fields.
The book begins with an introduction to Neural Networks and then covers the fundamentals of Python and the relevant libraries used in ANN modeling. Next, it gradually introduces the theoretical concepts that serve as the foundation for the rest of the book, including one-layer and multilayer neural networks, vectors and weights, and Linear Regression Models.
The core section of the book focuses on the construction of ANN models. It starts with building neural networks from scratch, including detailed coding examples. Then, the addition of input and output layers to the ANN model and techniques for saving, restoring, and fine-tuning the model's hyperparameters are discussed. Later, we discover the excellent TensorFlow library and how to write NN models using a high-level library.
In the book’s final part, readers will delve into training and compilation of DL models. Finally, the book concludes by demonstrating real-world applications of AI, providing readers with the necessary knowledge to grasp new AI concepts and engage in AI research while enabling them to implement and comprehend cutting-edge AI technologies.
By completing this book, readers will acquire the skills to effectively apply ANN in practice and develop a solid foundation for exploring advanced AI concepts and techniques.
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