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Python
Coraz więcej złożonych, powtarzalnych zadań powierzamy automatom. Inteligentny robot nigdy się nie znudzi, nie zmęczy i będzie cały czas pracował z zadaną prędkością. Zapewnia nam to odpowiednią wydajność i bardzo dużą dokładność wykonywanych czynności. Oczywiście aby osiągnąć te korzyści, najpierw trzeba robota zbudować i zaprogramować. Warto spróbować własnych sił w tej materii. Wiedza o programowaniu autonomicznych robotów jest coraz cenniejsza na rynku pracy, a samo budowanie robotów i ich programowanie może być niesamowicie interesującym hobby! Ta książka stanowi przystępne wprowadzenie do świata projektantów i budowniczych robotów. Dzięki niej dowiesz się, jak wybrać potrzebne podzespoły, jak je ze sobą połączyć i jak wykorzystywać poszczególne urządzenia wejścia i wyjścia. Posłużysz się w tym celu płytką Raspberry Pi i kompatybilnymi z nią podzespołami. Następnie napiszesz w Pythonie kod, dzięki któremu wzbogacisz swojego robota o sztuczną inteligencję i połączysz się z nim przez Wi-Fi za pomocą smartfonu. Zdobędziesz również wiedzę, w jaki sposób realizować bardziej złożone projekty z zakresu robotyki, a także przygotujesz się, aby zwizualizować, zaprojektować, zbudować i zaprogramować robota według własnego pomysłu. Z tą książką: skonfigurujesz Raspberry Pi pod kątem zbudowania robota ze sztuczną inteligencją podłączysz silniki i czujniki do Raspberry Pi zaprogramujesz inteligentnego robota wykorzystasz technologie rozpoznawania mowy i przetwarzania obrazu nauczysz się sterowania robotem ze sztuczną inteligencją przez Wi-Fi za pomocą smartfonu zaczniesz samodzielnie projektować i budować roboty Zbuduj i zaprogramuj inteligentnego robota!
Języki i paradygmaty programowania. Teoria i praktyka
Czym w rzeczywistości jest programowanie? I jak zacząć programować? Oprogramowanie jest dziś praktycznie wszędzie, a programiści od dawna należą do najbardziej poszukiwanych specjalistów. Na podstawie napisanego przez nich kodu funkcjonują już nie tylko komputery i smartfony. Oprogramowanie steruje sprzętami domowymi, telewizorem czy lodówką. W ramach tak zwanego internetu rzeczy wiele urządzeń technicznych komunikuje się między sobą bez udziału człowieka. Gwałtownie rozwija się sztuczna inteligencja, wymagająca specjalistycznego oprogramowania. Nie dziwi więc, że jego rozwój ciągle przyspiesza. W obliczu tych faktów odpowiedź na pytanie, jakiego języka programowania warto się nauczyć, jest trudna. Nawet dla osoby, która wie, w jaki sposób zamierza w przyszłości korzystać ze swoich informatycznych umiejętności. Autor książki proponuje nieco inne podejście do nauki programowania. Zachęca do zapoznania się z podstawowymi własnościami i możliwymi zastosowaniami kilku odległych od siebie, ale niezwykle ważnych aktualnie języków programowania, takich jak Python, Java SE, JavaScript i Prolog. W trakcie ich poznawania czytelnicy będą mieli okazję zgłębić filozofię programowania, a równocześnie zdobywać praktyczne umiejętności programistyczne na podstawowym poziomie. Starannie dobrany kod pokazuje możliwe zastosowania wybranych języków programowania. Pomoc w nauce stanowią też zadania do samodzielnego rozwiązania.
The release of Julia 1.0 is now ready to change the technical world by combining the high productivity and ease of use of Python and R with the lightning-fast speed of C++. Julia 1.0 programming gives you a head start in tackling your numerical and data problems. You will begin by learning how to set up a running Julia platform, before exploring its various built-in types. With the help of practical examples, this book walks you through two important collection types: arrays and matrices. In addition to this, you will be taken through how type conversions and promotions work. In the course of the book, you will be introduced to the homo-iconicity and metaprogramming concepts in Julia. You will understand how Julia provides different ways to interact with an operating system, as well as other languages, and then you'll discover what macros are. Once you have grasped the basics, you’ll study what makes Julia suitable for numerical and scientific computing, and learn about the features provided by Julia. By the end of this book, you will also have learned how to run external programs. This book covers all you need to know about Julia in order to leverage its high speed and efficiency for your applications.
LangChain in your Pocket. LangChain Essentials: From Basic Concepts to Advanced Applications
LangChain in your Pocket offers a detailed exploration into the LangChain framework, designed to enhance your skills in developing sophisticated language understanding models and applications. This book begins with the basics, introducing you to the fundamental concepts of LangChain through a simple Hello World example. As you progress, you'll delve into various LangChain modules, learning how to create agents, manage memory, and utilize output parsers effectively.The journey continues as you explore the RAG Framework, vector databases, and their applications in natural language processing, providing you with the tools to tackle common NLP problems efficiently. The book also addresses critical aspects of working with large language models (LLMs), such as prompt engineering, handling hallucinations, and evaluating model outputs. Advanced topics like autonomous AI agents and the integration of LangSmith and LangServe are covered, giving you a holistic view of what you can achieve with LangChain.By the end of this book, you will not only understand the technical aspects of LangChain but also how to apply these principles in real-world scenarios, making it an essential resource for anyone looking to advance their capabilities in AI and language processing.
Amazon SageMaker enables you to quickly build, train, and deploy machine learning models at scale without managing any infrastructure. It helps you focus on the machine learning problem at hand and deploy high-quality models by eliminating the heavy lifting typically involved in each step of the ML process. This second edition will help data scientists and ML developers to explore new features such as SageMaker Data Wrangler, Pipelines, Clarify, Feature Store, and much more.You'll start by learning how to use various capabilities of SageMaker as a single toolset to solve ML challenges and progress to cover features such as AutoML, built-in algorithms and frameworks, and writing your own code and algorithms to build ML models. The book will then show you how to integrate Amazon SageMaker with popular deep learning libraries, such as TensorFlow and PyTorch, to extend the capabilities of existing models. You'll also see how automating your workflows can help you get to production faster with minimum effort and at a lower cost. Finally, you'll explore SageMaker Debugger and SageMaker Model Monitor to detect quality issues in training and production.By the end of this Amazon book, you'll be able to use Amazon SageMaker on the full spectrum of ML workflows, from experimentation, training, and monitoring to scaling, deployment, and automation.
Learn Apache Mesos. A beginner’s guide to scalable cluster management and deployment
Apache Mesos is an open source cluster manager that provides efficient resource isolation and sharing across distributed applications or frameworks. This book will help you build a strong foundation of Mesos' capabilities along with practical examples to support the concepts explained throughout the book.Learn Apache Mesos dives straight into how Mesos works. You will be introduced to the distributed system and its challenges and then learn how you can use Mesos and its framework to solve data problems. You will also gain a full understanding of Mesos' internal mechanisms and get equipped to use Mesos and develop applications. Furthermore, this book lets you explore all the steps required to create highly available clusters and build your own Mesos frameworks. You will also cover application deployment and monitoring.By the end of this book, you will have learned how to use Mesos to make full use of machines and how to simplify data center maintenance.