A Quantitative ApproachComputer Architecture: A Quantitative Approach, has been considered essential reading by instructors, students and practitioners of computer design for nearly 30 years. The seventh edition of this classic textbook from John Hennessy and David Patterson, wWinner of a 2019 Textbook Excellence Award (Texty) from the Textbook and Academic Authors AssociationEach chapter follows a consistent framework: explanation of the ideas in each chapter; a "crosscutting issues" section, which presents how the concepts covered in one chapter connect with those given in other chapters; a "putting it all together" section that links these concepts by discussing how they are applied in real machine; and detailed examples of misunderstandings and architectural traps commonly encountered by developers and architectsIncludes "Putting It All Together" sections near the end of every chapter, providing real-world technology examples that demonstrate the principles covered in each chapterCovers new developments in GPU and CPU architectures, as well as domain specific architecturesFeatures more comprehensive coverage of systems on chip and heterogeneity

Deep learning made simple. Dip into deep learning without drowning in theory with this fully updated edition of Practical Deep Learning from experienced author and AI expert Ronald T. Kneusel. After a brief review of basic math and coding principles, you’ll dive into hands-on experiments and learn to build working models for everything from image analysis to creative writing, and gain a thorough understanding of how each technique works under the hood. Whether you’re a developer looking to add AI to your toolkit or a student seeking practical machine learning skills, this book will teach you: How neural networks work and how they’re trained How to use classical machine learning models How to develop a deep learning model from scratch How to evaluate models with industry-standard metrics How to create your own generative AI models Each chapter emphasizes practical skill development and experimentation, building to a case study that incorporates everything you’ve learned to classify audio recordings. Examples of working code you can easily run and modify are provided, and all code is freely available on GitHub. With Practical Deep Learning, second edition, you’ll gain the skills and confidence you need to build real AI systems that solve real problems. New to this edition: Material on computer vision, fine-tuning and transfer learning, localization, self-supervised learning, generative AI for novel image creation, and large language models for in-context learning, semantic search, and retrieval-augmented generation (RAG).

Immerse yourself in this indispensable resource for leaders tasked with the challenge of building or managing effective software development teams. This book is based on practical wisdom, offering actionable guidance to foster high-performing teams that excel in their projects. Despite the pivotal role leadership plays in a team's success, there aren't many companies that employ structured, best-practice-driven leadership methods. The core of the book covers several critical areas essential for any tech leader's success: building high-performance teams, project management, code quality, software design and architecture, software development life cycle (SDLC), software quality insurance, observability, technology and business alignment The relevance of structured, principled leadership in tech has never been more important. Tech Leadership Playbook aims to equip leaders with the knowledge and tools necessary to navigate the challenges of evolving business successfully. What You Will Learn Establish industry-proven strategies for building and sustaining high-performance teams Empower teams through mission driven ownership and autonomy Reduce development cost through effective leadership Implement real Agile project management culture Gain a solid understanding of different software design architectures Leverage architectural principles to design robust and maintainable software systems Improve Code Quality with strategic SDLC practices Who This Book is For Senior engineers, tech leaders, engineering managers, CTO, CIO, project managers, agile coaches, and founders