Miguel Angel Garcia, Barry Harmsen, Stephen Redmond, Karl Pover - książki
Tytuły autora: dostępne w księgarni Ebookpoint
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Data Science for Decision Makers. Enhance your leadership skills with data science and AI expertise
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Data Modeling with Microsoft Power BI
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Data Governance Handbook. A practical approach to building trust in data
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Python Data Cleaning Cookbook. Prepare your data for analysis with pandas, NumPy, Matplotlib, scikit-learn, and OpenAI - Second Edition
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LLM Prompt Engineering for Developers. The Art and Science of Unlocking LLMs' True Potential
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Dylemat sztucznej inteligencji. 7 zasad odpowiedzialnego tworzenia technologii
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Accelerate Model Training with PyTorch 2.X. Build more accurate models by boosting the model training process
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Fundamentals of Analytics Engineering. An introduction to building end-to-end analytics solutions
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The Definitive Guide to Data Integration. Unlock the power of data integration to efficiently manage, transform, and analyze data
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The Definitive Guide to Power Query (M). Mastering complex data transformation with Power Query
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Building Interactive Dashboards in Microsoft 365 Excel. Harness the new features and formulae in M365 Excel to create dynamic, automated dashboards
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Cracking the Data Science Interview. Unlock insider tips from industry experts to master the data science field
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Hands-On Entity Resolution
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Jak analizować dane z biblioteką Pandas. Praktyczne wprowadzenie. Wydanie II
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Data Observability for Data Engineering. Proactive strategies for ensuring data accuracy and addressing broken data pipelines
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Data Science for Web3. A comprehensive guide to decoding blockchain data with data analysis basics and machine learning cases
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Developing Kaggle Notebooks. Pave your way to becoming a Kaggle Notebooks Grandmaster
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Data Modeling with Microsoft Excel. Model and analyze data using Power Pivot, DAX, and Cube functions
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Machine Learning for Imbalanced Data. Tackle imbalanced datasets using machine learning and deep learning techniques
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Data Science: The Hard Parts
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Delta Lake: Up and Running
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Microsoft Power BI dla zaawansowanych. Eksperckie techniki tworzenia interaktywnych analiz w świecie biznesu. Wydanie II
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Microsoft Power BI. Jak modelować i wizualizować dane oraz budować narracje cyfrowe. Wydanie III
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Fundamentals of Data Observability
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Podręcznik architekta rozwiązań. Poznaj reguły oraz strategie projektu architektury i rozpocznij niezwykłą karierę. Wydanie II
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Azure Data and AI Architect Handbook. Adopt a structured approach to designing data and AI solutions at scale on Microsoft Azure
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Data Curious
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Uczenie maszynowe z użyciem Scikit-Learn, Keras i TensorFlow. Wydanie III
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Exploratory Data Analysis with Python Cookbook. Over 50 recipes to analyze, visualize, and extract insights from structured and unstructured data
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Zaufanie do systemów sztucznej inteligencji
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Sztuczna inteligencja od podstaw
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Building an Event-Driven Data Mesh
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DAX i Power BI w analizie danych. Tworzenie zaawansowanych i efektywnych analiz dla biznesu
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Sztuczna inteligencja. Nowe spojrzenie. Wydanie IV. Tom 1
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Sztuczna inteligencja. Nowe spojrzenie. Wydanie IV. Tom 2
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Dodaj mocy Power BI! Jak za pomocą kodu w Pythonie i R pobierać, przekształcać i wizualizować dane
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Microsoft Power BI Quick Start Guide. The ultimate beginner's guide to data modeling, visualization, digital storytelling, and more - Third Edition
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Data Quality Engineering in Financial Services
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Deep Learning. Praktyczne wprowadzenie z zastosowaniem środowiska Pythona
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Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow. 3rd Edition
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Data Cleaning and Exploration with Machine Learning. Get to grips with machine learning techniques to achieve sparkling-clean data quickly
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Mastering Microsoft Power BI. Expert techniques to create interactive insights for effective data analytics and business intelligence - Second Edition
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Deep learning z TensorFlow 2 i Keras dla zaawansowanych. Sieci GAN i VAE, deep RL, uczenie nienadzorowane, wykrywanie i segmentacja obiektów i nie tylko. Wydanie II
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Excel 2021 i Microsoft 365. Przetwarzanie danych za pomocą tabel przestawnych
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Practical Simulations for Machine Learning
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Microsoft Power BI. Jak modelować i wizualizować dane oraz budować narracje cyfrowe. Wydanie II
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Mastering Azure Machine Learning. Execute large-scale end-to-end machine learning with Azure - Second Edition
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The Tableau Workshop. A practical guide to the art of data visualization with Tableau
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Getting Started with Amazon SageMaker Studio. Learn to build end-to-end machine learning projects in the SageMaker machine learning IDE
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Time Series Analysis on AWS. Learn how to build forecasting models and detect anomalies in your time series data
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TinyML. Wykorzystanie TensorFlow Lite do uczenia maszynowego na Arduino i innych mikrokontrolerach
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Extreme DAX. Take your Power BI and Microsoft data analytics skills to the next level
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Intelligent Workloads at the Edge. Deliver cyber-physical outcomes with data and machine learning using AWS IoT Greengrass
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Azure Data Scientist Associate Certification Guide. A hands-on guide to machine learning in Azure and passing the Microsoft Certified DP-100 exam
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Extending Power BI with Python and R. Ingest, transform, enrich, and visualize data using the power of analytical languages
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Uczenie głębokie i sztuczna inteligencja. Interaktywny przewodnik ilustrowany
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Microsoft Power BI Cookbook. Gain expertise in Power BI with over 90 hands-on recipes, tips, and use cases - Second Edition
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Exploring GPT-3. An unofficial first look at the general-purpose language processing API from OpenAI
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Amazon Redshift Cookbook. Recipes for building modern data warehousing solutions
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Wzorce projektowe uczenia maszynowego. Rozwiązania typowych problemów dotyczących przygotowania danych, konstruowania modeli i MLOps
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Sztuczna inteligencja. Błyskawiczne wprowadzenie do uczenia maszynowego, uczenia ze wzmocnieniem i uczenia głębokiego
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Dane grafowe w praktyce. Jak technologie grafowe ułatwiają rozwiązywanie złożonych problemów
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Interactive Dashboards and Data Apps with Plotly and Dash. Harness the power of a fully fledged frontend web framework in Python – no JavaScript required
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Automated Machine Learning with Microsoft Azure. Build highly accurate and scalable end-to-end AI solutions with Azure AutoML
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Engineering MLOps. Rapidly build, test, and manage production-ready machine learning life cycles at scale
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Skazany na sukces. Kariera w Data Science
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Effortless App Development with Oracle Visual Builder. Boost productivity by building web and mobile applications efficiently using the drag-and-drop approach
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Umiejętności analityczne w pracy z danymi i sztuczną inteligencją. Wykorzystywanie najnowszych technologii w rozwijaniu przedsiębiorstwa
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Hurtownie danych. Od przetwarzania analitycznego do raportowania. Wydanie II
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Język R i analiza danych w praktyce. Wydanie II
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Uczenie maszynowe w aplikacjach. Projektowanie, budowa i wdrażanie
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Python Data Cleaning Cookbook. Modern techniques and Python tools to detect and remove dirty data and extract key insights
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Kubeflow Operations Guide
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Practical Fairness
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Codeless Deep Learning with KNIME. Build, train, and deploy various deep neural network architectures using KNIME Analytics Platform
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Microsoft Power BI Quick Start Guide. Bring your data to life through data modeling, visualization, digital storytelling, and more - Second Edition
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Machine Learning Design Patterns
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Praktyczne uczenie nienadzorowane przy użyciu języka Python
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Szeregi czasowe. Praktyczna analiza i predykcja z wykorzystaniem statystyki i uczenia maszynowego
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The Data Science Workshop. Learn how you can build machine learning models and create your own real-world data science projects - Second Edition
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Myślenie systemowe. Wprowadzenie
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Uczenie maszynowe z użyciem Scikit-Learn i TensorFlow. Wydanie II
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The Applied TensorFlow and Keras Workshop. Develop your practical skills by working through a real-world project and build your own Bitcoin price prediction tracker
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Building Machine Learning Pipelines
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Analytical Skills for AI and Data Science. Building Skills for an AI-Driven Enterprise
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Practical Synthetic Data Generation. Balancing Privacy and the Broad Availability of Data
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Hands-On Deep Learning with R. A practical guide to designing, building, and improving neural network models using R
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Hands-On Machine Learning with ML.NET. Getting started with Microsoft ML.NET to implement popular machine learning algorithms in C#
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The Practitioner's Guide to Graph Data. Applying Graph Thinking and Graph Technologies to Solve Complex Problems
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Data science od podstaw. Analiza danych w Pythonie. Wydanie II
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Algorytmy dla bystrzaków
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The Data Science Workshop. A New, Interactive Approach to Learning Data Science
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Building Machine Learning Powered Applications. Going from Idea to Product
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TinyML. Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers
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Machine Learning for Cybersecurity Cookbook. Over 80 recipes on how to implement machine learning algorithms for building security systems using Python
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Microsoft Excel 2019 Przetwarzanie danych za pomocą tabel przestawnych
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Korporacyjne jezioro danych. Wykorzystaj potencjał big data w swojej organizacji
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Praktyczne uczenie maszynowe
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arc42 by Example. Software architecture documentation in practice
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Developer, Advocate!. Conversations on turning a passion for talking about tech into a career
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Binary Analysis Cookbook. Actionable recipes for disassembling and analyzing binaries for security risks
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Practical Time Series Analysis. Prediction with Statistics and Machine Learning
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Deep Learning
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Machine Learning for OpenCV 4. Intelligent algorithms for building image processing apps using OpenCV 4, Python, and scikit-learn - Second Edition
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Hands-On Deep Learning with Go. A practical guide to building and implementing neural network models using Go
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Applied Unsupervised Learning with R. Uncover hidden relationships and patterns with k-means clustering, hierarchical clustering, and PCA
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Learn Chart.js. Create interactive visualizations for the Web with Chart.js 2
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The Enterprise Big Data Lake. Delivering the Promise of Big Data and Data Science
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Wprowadzenie do systemów baz danych. Wydanie VII
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Hands-On Deep Learning with Apache Spark. Build and deploy distributed deep learning applications on Apache Spark
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Python Machine Learning Blueprints. Put your machine learning concepts to the test by developing real-world smart projects - Second Edition
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Natural Language Processing with PyTorch. Build Intelligent Language Applications Using Deep Learning
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Python Deep Learning. Exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow - Second Edition
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QlikView: Advanced Data Visualization. Discover deeper insights with Qlikview by building your own rich analytical applications from scratch
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Applied Deep Learning on Graphs. Leveraging Graph Data to Generate Impact Using Specialized Deep Learning Architectures
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Python for Algorithmic Trading Cookbook. Recipes for designing, building, and deploying algorithmic trading strategies with Python
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Microsoft Power BI Cookbook. Turn data into strategic assets with updated techniques, features, use cases and best practices - Third Edition
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Responsible AI Made Easy with TensorFlow. The Ultimate Roadmap to Ethical AI: A Practical Guide to AI Fairness, Accountability, and Transparency
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Analiza statystyczna z IBM SPSS Statistics
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Cloud Analytics with Microsoft Azure. Build modern data warehouses with the combined power of analytics and Azure