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  • Build a Large Language Model (From Scratch)

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    How to implement LLM attention mechanisms and GPT-style transformers.In Build a Large Language Model (from Scratch) bestselling author Sebastian Raschka guides you step by step through creating your own LLM. Each stage is explained with clear text, diagrams, and examples. You’ll go from the initial design and creation, to pretraining on a general corpus, and on to fine-tuning for specific tasks Lesen Sie mehr

    49,44 €

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  • Hands-On Large Language Models

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    AI has acquired startling new language capabilities in just the past few years. Driven by the rapid advances in deep learning, language AI systems are able to write and understand text better than ever before. This trend enables the rise of new features, products, and entire industries. With this book, Python developers will learn the practical tools and concepts they need to use these Lesen Sie mehr

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  • AI Engineering

    Building Applications with Foundation Models

    von Chip Huyen
    Recent breakthroughs in AI have not only increased demand for AI products, they've also lowered the barriers to entry for those who want to build AI products. The model-as-a-service approach has transformed AI from an esoteric discipline into a powerful development tool that anyone can use. Everyone, including those with minimal or no prior AI experience, can now leverage AI models to build Lesen Sie mehr

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  • Designing Machine Learning Systems

    An Iterative Process for Production-Ready Applications

    von Chip Huyen
    Machine learning systems are both complex and unique. Complex because they consist of many different components and involve many different stakeholders. Unique because they're data dependent, with data varying wildly from one use case to the next. In this book, you'll learn a holistic approach to designing ML systems that are reliable, scalable, maintainable, and adaptive to changing environments Lesen Sie mehr

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  • LLM Engineer's Handbook

    Master the art of engineering large language models from concept to production

    Step into the world of LLMs with this practical guide that takes you from the fundamentals to deploying advanced applications using LLMOps best practices Get With Your Book: PDF Copy, AI Assistant, and Next-Gen Reader FreeKey FeaturesBuild and refine LLMs step by step, covering data preparation, RAG, and fine-tuningLearn essential skills for deploying and monitoring LLMs, ensuring optimal Lesen Sie mehr

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  • Prompt Engineering for Generative AI

    Large language models (LLMs) and diffusion models such as ChatGPT and Stable Diffusion have unprecedented potential. Because they have been trained on all the public text and images on the internet, they can make useful contributions to a wide variety of tasks. And with the barrier to entry greatly reduced today, practically any developer can harness LLMs and diffusion models to tackle problems Lesen Sie mehr

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  • The Software Engineer's Guidebook

    Navigating senior, tech lead, and staff engineer positions at tech companies and startups

    von Gergely Orosz
    In my first few years as a developer I assumed that hard work was all I needed. Then I was passed over for a promotion and my manager couldn’t give me feedback on what areas to improve, so I could get to the senior engineer level. I was frustrated; even bitter: not as much about missing the promotion, but because of the lack of guidance.By the time I became a manager, I was determined to support Lesen Sie mehr

    14,99 €

  • System Design Interview – An insider's guide

    von Alex Xu
    ( NOTE: THE ERROR ON THE E-BOOK FORMAT HAVE BEEN CORRECTED THANKS TO THE PREVIOUS REVIEW COMPLAINT SO ENJOY YOUR READ AND DON'T FORGET TO GIVE YOUR REVIEW) System design interviews are the most difficult to tackle of all technical interview questions. This book is Volume 1 of the System Design Interview - An insider’s guide series that provides a reliable strategy and knowledge base for Lesen Sie mehr

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  • Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow

    Through a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This bestselling book uses concrete examples, minimal theory, and production-ready Python frameworks (Scikit-Learn, Keras, and TensorFlow) Lesen Sie mehr

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  • Fundamentals of Data Engineering

    Plan and Build Robust Data Systems

    Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice. With this practical book, you'll learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available through the framework of the data engineering lifecycle Lesen Sie mehr

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  • Machine Learning Design Patterns

    The design patterns in this book capture best practices and solutions to recurring problems in machine learning. The authors, three Google engineers, catalog proven methods to help data scientists tackle common problems throughout the ML process. These design patterns codify the experience of hundreds of experts into straightforward, approachable advice.In this book, you will find detailed Lesen Sie mehr

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  • Practical Statistics for Data Scientists

    50+ Essential Concepts Using R and Python

    Statistical methods are a key part of data science, yet few data scientists have formal statistical training. Courses and books on basic statistics rarely cover the topic from a data science perspective. The second edition of this popular guide adds comprehensive examples in Python, provides practical guidance on applying statistical methods to data science, tells you how to avoid their misuse, Lesen Sie mehr

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