DZIEŃ PROGRAMISTY 2026 [Rabaty do -96%]
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Ta książka jest przeznaczona dla doświadczonych programistów C#, którzy chcą nauczyć się technik machine learning, deep learning i sztucznej inteligencji. Opisano tu dostępne narzędzia do uczenia maszynowego, dzięki którym można łatwo budować inteligentne aplikacje .NET wykorzystujące takie rozwiązania jak wykrywanie obrazów lub ruchu, wnioskowanie-
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Over the past two decades, the booming ecommerce and fintech industries have become a breeding ground for fraud. Organizations that conduct business online are constantly engaged in a cat-and-mouse game with these invaders. In this practical book, Gilit Saporta and Shoshana Maraney draw on their fraud-fighting experience to provide best practices,
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Niniejsza książka jest przydatnym przewodnikiem po uczeniu maszynowym i sieciach neuronowych. Zawiera praktyczne informacje, które doceni każdy programista stawiający pierwsze kroki w tej dziedzinie. Przedstawiono tu podstawy deep learningu i wyjaśniono takie pojęcia, jak strojenie sieci, wielowątkowość, wektoryzowanie danych. Opisano, w jaki sposó
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Unikalne wprowadzenie do nauki o danych! W dzisiejszych czasach najcenniejszym dobrem jest informacja. Ogromne ilości danych są przechowywane w przepastnych bazach danych, a kluczem do sukcesu jest ich umiejętna analiza i wyciąganie wniosków. To dynamicznie rozwijająca się dziedzina wiedzy, w której do tej pory brakowało solidnych pod
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SQL has evolved from a querying language for relational databases to a foundational tool for building scalable, modern data solutions across real-time analytics, machine learning workflows, and even generative AI applications. Advanced SQL moves beyond SELECT statements and taps into the full power of SQL as a programming interface for today's most
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Struggling to grasp machine learning concepts or unsure how to apply them in the real world? This book aims to change that by using the world's most popular game--soccer--to illuminate key concepts in predictive modeling and data science. You'll develop a solid foundation in machine learning through engaging examples that bridge academic principles
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Learn to use generative AI techniques to create novel text, images, audio, and even music with this practical, hands-on book. Readers will understand how state-of-the-art generative models work, how to fine-tune and adapt them to their needs, and how to combine existing building blocks to create new models and creative applications in different dom
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With demand for scaling, real-time access, and other capabilities, businesses need to consider building operational machine learning pipelines. This practical guide helps your company bring data science to life for different real-world MLOps scenarios. Senior data scientists, MLOps engineers, and machine learning engineers will learn how to tackle
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Since their introduction in 2017, transformers have quickly become the dominant architecture for achieving state-of-the-art results on a variety of natural language processing tasks. If you're a data scientist or coder, this practical book -now revised in full color- shows you how to train and scale these large models using Hugging Face Transformer
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Apache Spark is a ?exible in-memory framework that allows processing of both batch and real-time data. Its unified engine has made it quite popular for big data use cases. This book will help you to quickly get started with Apache Spark 2.0 and write efficient big data applications for a variety of use cases.
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This book will introduce the AI algorithms to the beginners and will take on implementing AI tasks using various Java-based libraries. It will take a practical approach to get you up and running with building smarter applications using Java programming knowledge.
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Large language models (LLMs) have transformed natural language processing, but deploying them in applications introduces numerous technical challenges. Large Language Models: The Hard Parts offers a clear, practical examination of the limitations developers and AI engineers face when building LLM-based applications. With a focus on implementation p
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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, ma
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W trakcie lektury poznasz najlepsze sposoby filtrowania danych, tworzenia rekomendacji, wykrywania grup oraz wyszukiwania i klasyfikowania. Na kolejnych stronach znajdziesz bogaty zbiór informacji poświęconych algorytmom analizującym dane. Ponadto będziesz mieć możliwość zapoznania się z różnymi sposobami optymalizacji, modelowania przy użyciu drze
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As businesses race to unlock the full potential of large language models (LLMs), a critical challenge has emerged: How do you connect these tools to real-time, external data to solve real-world problems? Retrieval-augmented generation (RAG) is the answer. By combining LLMs with information retrieval, RAG empowers you to build everything from intell
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Harness the power of MLOps for managing real time machine learning project cycle KEY FEATURES Comprehensive coverage of MLOps concepts, architecture, tools and techniques. Practical focus on building end-to-end ML Systems for Continual Learning with MLOps. Actionable insights on CI/CD, monitoring, continual model training and automated retrain
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Danologia to najszybciej rozwijająca się dziedzina na świecie. Przewiduje się, że do roku 2026 stworzy 11,5 mln nowych miejsc pracy, tak więc osoby poszukujące pracy i posiadające ten zestaw umiejętności mają tu wiele możliwości. Jednym z najbardziej pożądanych obszarów w dziedzinie danologii jest wydobywanie informacji ze stron internetowych. Jeśl
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Learn how to build an end-to-end data to AI solution on Google Cloud using Vertex AI KEY FEATURES Harness the power of AutoML capabilities to build machine learning models. Learn how to train custom machine learning models on the Google Cloud Platform. Accelerate your career in data analytics by leveraging the capabilities of GCP. DESCRIPTIO
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WPROWADZENIE DO UCZENIA MASZYNOWEGO Z WYKORZYSTANIEM INTUICYJNEGO JĘZYKA R Uczenie maszynowe i analiza danych pełnią coraz ważniejszą rolę w tworzeniu wartości dodanej. Uczenie maszynowe pozwala znajdować ukryte w danych zależności, wnosząc nowe pomysły i wiedzę, którą trudno byłoby osiągnąć bez tej zaawansowanej techniki. Książka Praktyc
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Accelerate the delivery of software, data, and machine learning KEY FEATURES Each chapter harmonizes the DevOps, Data Engineering, and Optimized Machine Learning cultures. Equips readers with AGILE skills to continuously re-prioritize production backlogs. Containerization, Docker, Kubernetes, DataOps, and MLOps are all rolled together. DESCRI
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Rozwijaj i replikuj interesujące eksperymenty uczenia maszynowego (ML) przy użyciu kamery Pi Camera i płytki Raspberry Pi. Niniejsza książka zapewnia solidny przegląd technik uczenia maszynowego i niezliczonych zagadnień leżących u jego podstaw, zachęcając do ich dalszego poznawania. Nietechniczne omówienia równoważą złożone objaśnien
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Opanuj skuteczne, gotowe do użycia rozwiązania biznesowe dla sztucznej inteligencji i uczenia maszynowego AI podejście pragmatyczne pomaga rozwiązywać praktyczne problemy przy użyciu nowoczesnego uczenia maszynowego, sztucznej inteligencji i chmurowych narzędzi obliczeniowych. Noah Gift demistyfikuje wszelkie koncepcje i narzędzia potrzebne do osią
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Ta praktyczna książka ułatwi Ci rozpoczęcie wdrażania rozwiązań rzeczywistych problemów związanych z uczeniem maszynowym. Zawiera przystępne wprowadzenie do uczenia maszynowego i sztucznej inteligencji, a także sposoby wykorzystania Pythona i biblioteki scikit-learn, uwzględniające potrzeby badaczy i analityków danych oraz inżynierów pracujących na
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To książka przeznaczona dla programistów i menedżerów, którzy wśród rodzących się idei uczenia maszynowego wciąż poszukują rozwiązań dla swojego biznesu. Autor omawia krok po kroku proces tworzenia i wdrażania aplikacji opartej na uczeniu maszynowym, a praktyczne koncepcje przedstawia za pomocą przykładowych kodów, rysunków i wywiadów z liderami w
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Ta książka jest przeznaczona dla praktyków, przede wszystkim programistów, architektów i naukowców, którzy chcą się nauczyć projektowania systemów uczących. Podstawowe pojęcia dotyczące uczenia maszynowego wyjaśniono tu poprzez praktyczne przykłady. Przedstawiono możliwości TensorFlow jako systemu do przeprowadzania obliczeń na tensorach. Omówiono
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Ta książka jest praktycznym przewodnikiem, który ułatwia wdrażanie architektury jeziora danych (ang. data lake) w przedsiębiorstwie. Omówiono tu różne podejścia do jej uruchamiania i rozwijania, w tym kałuże danych (analityczne piaskownice) i stawy danych (hurtownie danych), a także budowanie jezior danych od podstaw. Opisano konfigurowanie różnych
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Dowiesz się, jak dzięki danym z mediów społecznościowych określić sieć powiązań użytkowników, zorientować się, kto o czym mówi i gdzie się znajduje. Treść bogato zilustrowano przykładami kodu w Pythonie, a także plikami Jupyter Notebook lub kontenerów Dockera. Ciekawym elementem książki jest zbiór receptur dotyczących rozwiązywania konkretnych prob
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Ta książka jest znakomitym przewodnikiem po technikach uczenia głębokiego. Poza wyczerpująco przedstawionymi podstawami znajdziesz tu zasady implementacji tych technik z wykorzystaniem języka R i biblioteki Keras. Dzięki przystępnym wyjaśnieniom i praktycznym przykładom szybko zrozumiesz nawet bardziej skomplikowane zagadnienia uczenia głębokiego.
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Niniejsza książka jest doskonałym wprowadzeniem do nauki o danych. Jej autorzy wskażą Ci prostą i szybką drogę do rozwiązywania różnych problemów z tego obszaru za pomocą Pythona oraz powiązanych z nim pakietów do analizy danych i uczenia maszynowego. Dzięki lekturze przejdziesz przez kolejne etapy modyfikowania i wstępnego przetwarzania danych, po
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Niniejsza książka jest przeznaczona dla osób, które chcą projektować inteligentne algorytmy, a przy tym mają podstawy z zakresu programowania, matematyki i statystyki. Przedstawiono tu schematy projektowe i praktyczne przykłady rozwiązań. Opisano algorytmy, które przetwarzają strumienie danych pochodzące z internetu, a także systemy rekomendacji i
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Bridge the gap between cutting edge research and the practical operationalization of generative AI. This handy guide demystifies the complexities of managing GenAI applications using leading open source platform MLflow on Databricks. What sets this book apart is its focus on the requirements of managing and deploying GenAI applications. ML and AI
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MLOps engineers have to deal with a glut of tools and SaaS applications, not to mention technical debt clogging the system. Such complexity requires a comprehensive approach. The Databricks platform provides all the critical components for end-to-end MLOps and LLMOps in one place. This exhaustive book shows you how to use Databricks to build and ma
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Video generation is rapidly becoming a key area in generative AI, combining spatial, temporal, and multimodal reasoning to produce moving images that are both coherent and creative. For many practitioners, however, understanding how these models function and implementing them remains a significant challenge. Video Generation with AI offers a straig
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La IA ha adquirido nuevas y sorprendentes capacidades lingüísticas en los últimos ańos. Impulsados por los rápidos avances en Deep Learning, los sistemas de IA lingüística son capaces de escribir y comprender textos mejor que nunca. Esta tendencia está dando lugar a nuevas funciones, productos e industrias enteras. A través de la naturaleza visualm
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As generative AI becomes central to modern data and machine learning workflows, earning the Databricks Certified Generative AI Engineer Associate certification signals both credibility and technical fluency. This study guide prepares you for this sought-after certification with comprehensive coverage of core GenAI and LLM concepts, practical data m
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Learning AutoML is your practical guide to applying automated machine learning in real-world environments. Whether you're a data scientist, ML engineer, or AI researcher, this book helps you move beyond experimentation to build and deploy high-performing models with less manual tuning and more automation. Using AutoGluon as a primary toolkit, you'l
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The vast potential of AI technology remains untapped in areas like audio, video, and complex data analysis. In fact, many of today's professionals find it challenging to apply AI innovations across these diverse domains due to a lack of guidance and practical implementations.This comprehensive guide, tailored especially for intermediate to advanced
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Navigating the complexities of large-scale spatial data can be daunting. In order to unleash the power of massive and complex datasets, you'll need a cutting-edge tool like Apache Sedona. This innovative distributed computing system, designed specifically for spatial data, has diverse applications in fields such as mobility, telematics, agriculture
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Elevate your AI system performance capabilities with this definitive guide to maximizing efficiency across every layer of your AI infrastructure. In today's era of ever-growing generative models, AI Systems Performance Engineering provides engineers, researchers, and developers with a hands-on set of actionable optimization strategies. Learn to co-
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Get up to speed on a new unified approach to building machine learning (ML) systems with a feature store. Using this practical book, data scientists and ML engineers will learn in detail how to develop and operate batch, real-time, and agentic ML systems. Author Jim Dowling introduces fundamental principles and practices for developing, testing, an
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In the era of big data and even bigger machine learning models powering the current generative AI revolution, the environmental footprint of these developments can no longer be ignored. This much-needed guide confronts the challenge head-on, offering a groundbreaking exploration into making deep learning (DL) both efficient and accessible. Author R
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As Snowflake's capabilities expand, staying updated with its latest features and functionalities can be overwhelming. The platform's rapid development gave rise to advanced tools like Snowpark and the Native App Framework, which are crucial for optimizing data operations but may seem complex to navigate. In this essential book, author Muhammad Fasi
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This book provides a beginner-friendly introduction to AI and Machine Learning. Through clear explanations and Python tutorials, it covers deep learning, NLP, and ethical AI, helping readers gain practical knowledge for real-world applications.
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This accessible guide covers Python fundamentals and core machine learning concepts. Ideal for complete beginners looking to break into tech and data science.
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AI is transforming industries, and cloud-based AI expertise is in high demand. This study guide is your essential resource for mastering foundational AI concepts and AWS tools while preparing for the AIF-C01 certification exam. Author Tom Taulli breaks down complex topics into practical, easy-to-understand lessons that will enhance the test-readine
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Tackle the core challenges related to enterprise-ready graph representation and learning. With this hands-on guide, applied data scientists, machine learning engineers, and practitioners will learn how to build an E2E graph learning pipeline. You'll explore core challenges at each pipeline stage, from data acquisition and representation to real-tim
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Feeling overwhelmed by the volume of data in your research? Sifting through massive amounts of data to find useful insights is becoming increasingly difficult in drug discovery, genetics, and healthcare. Enter the era of generative AI with LangChain, whose groundbreaking tools are changing the way life scientists and researchers operate. In this g
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Eager to learn AI and machine learning but unsure where to start? Laurence Moroney's hands-on, code-first guide demystifies complex AI concepts without relying on advanced mathematics. Designed for programmers, it focuses on practical applications using PyTorch, helping you build real-world models without feeling overwhelmed. From computer vision
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Businesses that want to stay competitive know that AI has become a crucial technology—and so do their employees looking to grow their careers. Earning Microsoft's AI-900: Azure AI Fundamentals certification proves your proficiency with foundational AI concepts. This study guide equips you with the knowledge needed to pass the AI-900 exam, whe
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Large language models (LLMs) have proven themselves to be powerful tools for solving a wide range of tasks, and enterprises have taken note. But transitioning from demos and prototypes to full-fledged applications can be difficult. This book helps close that gap, providing the tools, techniques, and playbooks that practitioners need to build useful
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This book explores the foundations of probability and statistics, guiding readers through key concepts like distributions, hypothesis testing, Bayesian models, and Markov processes. Essential for machine learning.
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A comprehensive introduction to artificial intelligence engines focusing on the mathematics behind neural networks and deep learning, featuring practical examples and hands-on approaches to key AI techniques.
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This book offers a detailed introduction to information theory, covering entropy, coding, and data compression. It explores advanced topics like noisy channels, rate distortion, and the connection between information and thermodynamics.
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Information Theory. A Tutorial Introduction to the Principles and Applications of Information Theory
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Explore the essentials of linear regression using Python, covering topics like finding the best-fitting line, assessing statistical significance, and advanced methods such as Bayesian regression, all supported by Python code examples.
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Master calculus fundamentals essential for AI and machine learning. This guide covers derivatives, integrals, limits, and multivariable calculus, emphasizing applications in neural networks, optimization, and data science techniques.
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Large language models (LLMs) are revolutionizing the world, promising to automate tasks and solve complex problems. A new generation of software applications are using these models as building blocks to unlock new potential in almost every domain, but reliably accessing these capabilities requires new skills. This book will teach you the art and sc
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Reinforcement learning (RL) has led to several breakthroughs in AI. The use of the Q-learning (DQL) algorithm alone has helped people develop agents that play arcade games and board games at a superhuman level. More recently, RL, DQL, and similar methods have gained popularity in publications related to financial research.This book is among the fir
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Using machine learning for products, services, and critical business processes is quite different from using ML in an academic or research setting—especially for recent ML graduates and those moving from research to a commercial environment. Whether you currently work to create products and services that use ML, or would like to in the future
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Large language models (LLMs) and generative AI are rapidly changing the healthcare industry. These technologies have the potential to revolutionize healthcare by improving the efficiency, accuracy, and personalization of care. This practical book shows healthcare leaders, researchers, data scientists, and AI engineers the potential of LLMs and gene
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Bringing a deep-learning project into production at scale is quite challenging. To successfully scale your project, a foundational understanding of full stack deep learning, including the knowledge that lies at the intersection of hardware, software, data, and algorithms, is required.This book illustrates complex concepts of full stack deep learnin
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This course demystifies complex topics, providing you with a solid foundation in data analysis and algorithm optimization. Perfect for technical professionals aiming to enhance their understanding and application of machine learning.
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Learn the core concepts of linear algebra essential for machine learning. This course guides you through vectors, matrices and their applications culminating in principal component analysis, making it a perfect guide for beginners and professionals.
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The surging predictive analytics market is expected to grow from $10.5 billion today to $28 billion by 2026. With the rise in automation across industries, the increase in data-driven decision-making, and the proliferation of IoT devices, predictive analytics has become an operational necessity in today's forward-thinking companies.If you're a data
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Many organizations today analyze and share large, sensitive datasets about individuals. Whether these datasets cover healthcare details, financial records, or exam scores, it's become more difficult for organizations to protect an individual's information through deidentification, anonymization, and other traditional statistical disclosure limitati
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Advance your Power BI skills by adding AI to your repertoire at a practice level. With this practical book, business-oriented software engineers and developers will learn the terminologies, practices, and strategy necessary to successfully incorporate AI into your business intelligence estate. Jen Stirrup, CEO of AI and BI leadership consultancy Da
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Dive into machine learning with our course, designed to guide you in building your own recommender system using Scikit-Learn, complete with practical datasets and ethical considerations.
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Dive into the world of Machine Learning with Python, exploring essential algorithms, data scrubbing techniques, and model design to unlock the potential of AI and data science.
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Approach data science interviews with confidence with this one-stop guide focused on Python programming, SQL, shell/bash, version control, statistics, and ML modeling. No need to scan the internet for technical interview prep material—it's all here!
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Gain the valuable skills and techniques you need to accelerate the delivery of machine learning solutions. With this practical guide, data scientists, ML engineers, and their leaders will learn how to bridge the gap between data science and Lean product delivery in a practical and simple way. David Tan, Ada Leung, and Dave Colls show you how to app
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Entity resolution is a key analytic technique that enables you to identify multiple data records that refer to the same real-world entity. With this hands-on guide, product managers, data analysts, and data scientists will learn how to add value to data by cleansing, analyzing, and resolving datasets using open source Python libraries and cloud API
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The world's businesses ingest a combined 2.5 quintillion bytes of data every day. But how much of this vast amount of data--used to build products, power AI systems, and drive business decisions--is poor quality or just plain bad? This practical book shows you how to ensure that the data your organization relies on contains only high-quality record
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Deep learning is rapidly gaining momentum in the world of finance and trading. But for many professional traders, this sophisticated field has a reputation for being complex and difficult. This hands-on guide teaches you how to develop a deep learning trading model from scratch using Python, and it also helps you create and backtest trading algorit
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Unlocking computer vision with Python and OpenCV KEY FEATURES Practical solutions to image processing challenges. Detect and classify objects in images. Recognize faces and text from images using character detection and recognition models. DESCRIPTION Neural Network Computer Vision with OpenCV equips you with professional skills and knowledg
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Unveiling the power and potential of Generative AI for a limitless future KEY FEATURES Holistic and accessible journey into Generative AI. Indispensable guide for unleashing Generative AI potential. Transforming technology, business, art, and innovation, covering technological advancements and business optimization. DESCRIPTION The Potential
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Implementing and designing systems that make suggestions to users are among the most popular and essential machine learning applications available. Whether you want customers to find the most appealing items at your online store, videos to enrich and entertain them, or news they need to know, recommendation systems (RecSys) provide the way.In this
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As tech products become more prevalent today, the demand for machine learning professionals continues to grow. But the responsibilities and skill sets required of ML professionals still vary drastically from company to company, making the interview process difficult to predict. In this guide, data science leader Susan Shu Chang shows you how to tac
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Your training data has as much to do with the success of your data project as the algorithms themselves because most failures in AI systems relate to training data. But while training data is the foundation for successful AI and machine learning, there are few comprehensive resources to help you ace the process. In this hands-on guide, author Anth
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This practical guide provides a collection of techniques and best practices that are generally overlooked in most data engineering and data science pedagogy. A common misconception is that great data scientists are experts in the "big themes" of the discipline—machine learning and programming. But most of the time, these tools can only take u
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Unlock the power of AI with Python: Your Journey from Novice to Neural Nets KEY FEATURES Learn to code in Python and use Google Colab's hardware accelerators (GPU and TPU) to train and deploy AI models efficiently. Develop Convolutional Neural Networks (CNNs) using the TensorFlow 2 library for computer vision tasks. Develop sequence, attention
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Learn how to build a complete machine learning pipeline by mastering feature extraction, feature selection, and algorithm training KEY FEATURES Develop a solid understanding of foundational principles in machine learning. Master regression and classification methods for accurate data prediction and categorization in machine learning. Dive into
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All cloud architects need to know how to build data platforms that enable businesses to make data-driven decisions and deliver enterprise-wide intelligence in a fast and efficient way. This handbook shows you how to design, build, and modernize cloud native data and machine learning platforms using AWS, Azure, Google Cloud, and multicloud tools li
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Learn using Cloud data technologies for improving data analytics and decision-making capabilities for your organization KEY FEATURES Get familiar with the fundamentals of data architecture and Cloud computing. Design and deploy enterprise data architectures on the Cloud. Learn how to leverage AI/ML to gain insights from data. DESCRIPTION Clo
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As an aspiring data scientist, you appreciate why organizations rely on data for important decisions--whether it's for companies designing websites, cities deciding how to improve services, or scientists discovering how to stop the spread of disease. And you want the skills required to distill a messy pile of data into actionable insights. We call
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Take a data-first and use-case–driven approach with Low-Code AI to understand machine learning and deep learning concepts. This hands-on guide presents three problem-focused ways to learn no-code ML using AutoML, low-code using BigQuery ML, and custom code using scikit-learn and Keras. In each case, you'll learn key ML concepts by using real-
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A hands-on guide to building and deploying deep learning models with Python KEY FEATURES Acquire the skills to perform exploratory data analysis, uncover insights, and preprocess data for deep learning tasks. Build and train various types of neural networks, including Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs). G
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There are several reasons why probabilistic machine learning represents the next-generation ML framework and technology for finance and investing. This generative ensemble learns continually from small and noisy financial datasets while seamlessly enabling probabilistic inference, retrodiction, prediction, and counterfactual reasoning. Probabilisti
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This practical guide provides more than 200 self-contained recipes to help you solve machine learning challenges you may encounter in your work. If you're comfortable with Python and its libraries, including pandas and scikit-learn, you'll be able to address specific problems, from loading data to training models and leveraging neural networks.Each
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AI is a tool that demands a deeper understanding of where and how to use it. By becoming Citizens of Data Science, we can actively participate in where and how AI is used to improve the human condition. With the help of this guide, you'll get to grips with the relevant AI and data concepts that will help you make the most of the AI revolution.
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With the rapid rise of graph databases, organizations are now implementing advanced analytics and machine learning solutions to help drive business outcomes. This practical guide shows data scientists, data engineers, architects, and business analysts how to get started with a graph database using TigerGraph, one of the leading graph database model
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Incredibly useful, knowledge graphs help organizations keep track of medical research, cybersecurity threat intelligence, GDPR compliance, web user engagement, and much more. They do so by storing interlinked descriptions of entities—objects, events, situations, or abstract concepts—and encoding the underlying information. How do you cr
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Learn how to deploy complex machine learning models on single board computers, mobile phones, and microcontrollers KEY FEATURES Gain a comprehensive understanding of TinyML's core concepts. Learn how to design your own TinyML applications from the ground up. Explore cutting-edge models, hardware, and software platforms for developing TinyML.
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A guide to understand the basics of machine learning and its application in the field of education KEY FEATURES Create a more efficient and effective learning environment that meets the needs of all students. Learn how to use the profound Machine learning advancements in the field of education. Understand how students can use machine learning
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A comprehensive guide to Deep Learning for Beginners KEY FEATURES Learn how to design your own neural network efficiently. Learn how to build and train Recurrent Neural Networks (RNNs). Understand how encoding and decoding work in Deep Neural Networks. DESCRIPTION Deep Learning has become increasingly important due to the growing need to pro
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Between major privacy regulations like the GDPR and CCPA and expensive and notorious data breaches, there has never been so much pressure to ensure data privacy. Unfortunately, integrating privacy into data systems is still complicated. This essential guide will give you a fundamental understanding of modern privacy building blocks, like differenti
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The past decade has witnessed the broad adoption of artificial intelligence and machine learning (AI/ML) technologies. However, a lack of oversight in their widespread implementation has resulted in some incidents and harmful outcomes that could have been avoided with proper risk management. Before we can realize AI/ML's true benefit, practitioners
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A step-by-step guide that will teach you how to deploy TinyML on microcontrollers KEY FEATURES Deploy machine learning models on edge devices with ease. Leverage pre-built AI models and deploy them without writing any code. Create smart and efficient IoT solutions with TinyML. DESCRIPTION TinyML, or Tiny Machine Learning, is used to enable m
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A multifaceted approach to develop an understanding of AI and its potential applications KEY FEATURES AI-informed focuses on AI foundation, applications, and methodologies. AI-inquired focuses on computational thinking and bias awareness. AI-innovate focuses on creative and critical thinking and the Capstone project. DESCRIPTION AI is a dis
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Learn how to use AutoML to leverage Machine Learning for solving business problems KEY FEATURES Get familiar with the common machine learning problems and understand how to solve them. Understand the importance of different types of data and how to work with them effectively. Learn how to use machine learning and AutoML tools to solve real-wor
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A complete guide that will help you get familiar with Machine Learning models, algorithms, and optimization techniques KEY FEATURES Understand the core concepts and algorithms of Machine Learning. Get started with your Machine Learning career with this easy-to-understand guide. Discover different Machine Learning use cases across different dom
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Learn how to build end-to-end scalable machine learning solutions with Apache Spark. With this practical guide, author Adi Polak introduces data and ML practitioners to creative solutions that supersede today's traditional methods. You'll learn a more holistic approach that takes you beyond specific requirements and organizational goals--allowing d
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A practical guide that will help you build AI and ML solutions faster with fewer efforts and no programming knowledge KEY FEATURES Start your journey to become an AI expert today. Learn how to build AI solutions to solve complex problems in your organization. Get familiar with different No-code AI tools and platforms. DESCRIPTION No-Code Ar
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This is a practical workbook that analyzes past Kaggle competitions in hopes of helping readers understand the best practices on how to approach future challenges. With the help of this workbook, readers will experience the case studies as if they themselves were part of the competitions and gain hands-on experience on how to approach their first K
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Bring elasticity and innovation to Machine Learning and AI operations KEY FEATURES Coverage includes a wide range of AWS AI and ML services to help you speedily get fully operational with ML. Packed with real-world examples, practical guides, and expert data science methods for improving AI/ML education on AWS. Includes ready-made, purpose-bui
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Get started with Ray, the open source distributed computing framework that simplifies the process of scaling compute-intensive Python workloads. With this practical book, Python programmers, data engineers, and data scientists will learn how to leverage Ray locally and spin up compute clusters. You'll be able to use Ray to structure and run machine
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Explore different web mining techniques to discover patterns, structures, and information from the web KEY FEATURES A complete overview of the basic and advanced concepts of Web mining. Work with easy-to-use open-source Python libraries for Web mining. Get familiar with the various beneficial areas and applications of Web mining. DESCRIPTION
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Explore the Essential Concepts, Tools, and Services in GCP KEY FEATURES Build a solid foundation of the Google Cloud Platform. Work with different AI and Machine Learning services offered by Google Cloud. Learn how to use Google cloud services to build scalable apps. DESCRIPTION Google Cloud platform has a suite of cloud computing services f
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Edge AI is transforming the way computers interact with the real world, allowing IoT devices to make decisions using the 99% of sensor data that was previously discarded due to cost, bandwidth, or power limitations. With techniques like embedded machine learning, developers can capture human intuition and deploy it to any target--from ultra-low pow
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Companies are scrambling to integrate AI into their systems and operations. But to build truly successful solutions, you need a firm grasp of the underlying mathematics. This accessible guide walks you through the math necessary to thrive in the AI field such as focusing on real-world applications rather than dense academic theory.Engineers, data s
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With the increasing use of AI in high-stakes domains such as medicine, law, and defense, organizations spend a lot of time and money to make ML models trustworthy. Many books on the subject offer deep dives into theories and concepts. This guide provides a practical starting point to help development teams produce models that are secure, more robus
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A step-by-step guide to get started with Machine Learning KEY FEATURES Understand different types of Machine Learning like Supervised, Unsupervised, Semi-supervised, and Reinforcement learning. Learn how to implement Machine Learning algorithms effectively and efficiently. Get familiar with the various libraries & tools for Machine Learning.
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Python is a first-class tool for many researchers, primarily because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the new edition of Python Data Science Handbook do you get them all--IPython, NumPy, pandas, Matplotlib, scikit-learn,
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Unlock the Potential of Data Science and Machine Learning to Your Business and Organization KEY FEATURES Includes today's most popular applications powered by data science and machine learning technology. A solid primer on the entire data science lifecycle, detailed with examples. An integrated approach to demonstrating the use of Image Proces
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This practical guide bridges the gap between general cloud computing architecture in Microsoft Azure and scientific computing for bioinformatics and genomics. You'll get a solid understanding of the architecture patterns and services that are offered in Azure and how they might be used in your bioinformatics practice. You'll get code examples that
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While many introductory guides to AI are calculus books in disguise, this one mostly eschews the math. Instead, author Jeff Prosise helps engineers and software developers build an intuitive understanding of AI to solve business problems. Need to create a system to detect the sounds of illegal logging in the rainforest, analyze text for sentiment,
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Most intermediate-level machine learning books focus on how to optimize models by increasing accuracy or decreasing prediction error. But this approach often overlooks the importance of understanding why and how your ML model makes the predictions that it does.Explainability methods provide an essential toolkit for better understanding model behavi
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If you want to work in any computational or technical field, you need to understand linear algebra. As the study of matrices and operations acting upon them, linear algebra is the mathematical basis of nearly all algorithms and analyses implemented in computers. But the way it's presented in decades-old textbooks is much different from how professi
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Healthcare is the next frontier for data science. Using the latest in machine learning, deep learning, and natural language processing, you'll be able to solve healthcare's most pressing problems: reducing cost of care, ensuring patients get the best treatment, and increasing accessibility for the underserved. But first, you have to learn how to ac
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Explore the IoT with other emerging technologies like Artificial Intelligence, Machine Learning, Cloud Computing, and Blockchain Technology KEY FEATURES Learn from the basics of Internet of Everything, Industry 4.0, and Society 5.0. Check your knowledge with self-assessment questions and case studies. Supports the Government of India project D
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Introducing Practical Smart Agents Development using Python, PyTorch, and TensorFlow KEY FEATURES Exposure to well-known RL techniques, including Monte-Carlo, Deep Q-Learning, Policy Gradient, and Actor-Critical. Hands-on experience with TensorFlow and PyTorch on Reinforcement Learning projects. Everything is concise, up-to-date, and visually
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Get going with tidymodels, a collection of R packages for modeling and machine learning. Whether you're just starting out or have years of experience with modeling, this practical introduction shows data analysts, business analysts, and data scientists how the tidymodels framework offers a consistent, flexible approach for your work.RStudio enginee
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