Neural Networks From Scratch By Harrison Kinsley

Neural Networks from Scratch in Python

Practical Generative AI with ChatGPT

Transform your professional world with ChatGPT and OpenAI—master prompt design to revolutionize development, marketing, research, and enterprise implementation Key Features Turn ChatGPT into your companion for marketing, research, personal productivity, art and coding Learn prompt engineering techniques that deliver consistent, relevant, and ethical AI-powered results Build custom GPTs and assistants tailored to your specific business needs and workflows Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionPractical Generative AI with ChatGPT is your hands-on guide to unlocking the full potential of ChatGPT. From building AI assistants and mastering prompt engineering to analyzing documents and images and even generating code, this book equips you with the skills to integrate generative AI into your workflow. Written by a technical architect specializing in AI and intelligent applications, this book provides the tools and knowledge you need to streamline tasks, enhance productivity, and create intelligent solutions. You’ll learn how to craft precise prompts, leverage ChatGPT for daily efficiency, and develop custom AI assistants tailored to your needs. The chapters show you how to use ChatGPT’s multimodal capabilities to generate images with DALL·E and even transform images into code. This ChatGPT book goes beyond basic interactions by showing you how to design custom GPTs and integrate OpenAI’s APIs into your applications. You’ll explore how businesses use OpenAI models, from building AI applications, including semantic search, to creating an AI roadmap. Each chapter is packed with practical examples, ensuring you can apply the techniques right away. By the end of this book, you’ll be well equipped to leverage OpenAI's technology for competitive advantage.What you will learn Explore the fundamentals of generative AI and GPT models Master prompt engineering to consistently get relevant and reliable outputs from ChatGPT Develop marketing strategies and conduct meaningful A/B testing with AI assistance Boost your coding with code generation, review, and optimization Enhance research with real-time knowledge mining Enhance your visual creativity with image generation, image understanding, and style transfer Design custom GPTs and assistants tailored to specific business functions Discover how enterprises are leveraging large language models for their AI apps Who this book is for This book is ideal for business professionals, developers, marketers, researchers, and decision-makers who want to leverage AI to enhance productivity. No advanced technical background is required for the foundational sections, making the content accessible to beginners, while later chapters provide depth for technical professionals implementing enterprise solutions. If you’re seeking practical applications of generative AI in business contexts, you’ll find immediate, actionable value in this book.

Deep Learning from Scratch

With the resurgence of neural networks in the 2010s, deep learning has become essential for machine learning practitioners and even many software engineers. This book provides a comprehensive introduction for data scientists and software engineers with machine learning experience. You’ll start with deep learning basics and move quickly to the details of important advanced architectures, implementing everything from scratch along the way. Author Seth Weidman shows you how neural networks work using a first principles approach. You’ll learn how to apply multilayer neural networks, convolutional neural networks, and recurrent neural networks from the ground up. With a thorough understanding of how neural networks work mathematically, computationally, and conceptually, you’ll be set up for success on all future deep learning projects. This book provides: Extremely clear and thorough mental models—accompanied by working code examples and mathematical explanations—for understanding neural networks Methods for implementing multilayer neural networks from scratch, using an easy-to-understand object-oriented framework Working implementations and clear-cut explanations of convolutional and recurrent neural networks Implementation of these neural network concepts using the popular PyTorch framework