Marleen Meier, David Baldwin, Kate Strachnyi - książki
Tytuły autora: dostępne w księgarni Ebookpoint
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Getting Started with DuckDB. A practical guide for accelerating your data science, data analytics, and data engineering workflows
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Uczenie maszynowe w języku R. Tworzenie i doskonalenie modeli - od przygotowania danych po dostrajanie, ewaluację i pracę z big data. Wydanie IV
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Augmented Analytics
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Data Governance Handbook. A practical approach to building trust in data
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Before Machine Learning Volume 1 - Linear Algebra for A.I. The Fundamental Mathematics for Data Science and Artificial Intelligence
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Predictive Analytics for the Modern Enterprise
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Databricks ML in Action. Learn how Databricks supports the entire ML lifecycle end to end from data ingestion to the model deployment
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Data Analytics for Marketing. A practical guide to analyzing marketing data using Python
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Uczenie maszynowe w Pythonie. Receptury. Od przygotowania danych do deep learningu. Wydanie II
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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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Dancing with Qubits. From qubits to algorithms, embark on the quantum computing journey shaping our future - Second Edition
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Machine Learning: Make Your Own Recommender System. Build Your Recommender System with Machine Learning Insights
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Machine Learning with Python. Unlocking AI Potential with Python and Machine Learning
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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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Data-Centric Machine Learning with Python. The ultimate guide to engineering and deploying high-quality models based on good data
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Learn Microsoft Fabric. A practical guide to performing data analytics in the era of artificial intelligence
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Bayesian Analysis with Python. A practical guide to probabilistic modeling - Third Edition
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Data Engineering with Scala and Spark. Build streaming and batch pipelines that process massive amounts of data using Scala
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MLOps with Red Hat OpenShift. A cloud-native approach to machine learning operations
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MATLAB for Machine Learning. Unlock the power of deep learning for swift and enhanced results - Second Edition
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Deep Learning for Finance
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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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The Definitive Guide to Google Vertex AI. Accelerate your machine learning journey with Google Cloud Vertex AI and MLOps best practices
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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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Vector Search for Practitioners with Elastic. A toolkit for building NLP solutions for search, observability, and security using vector search
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Practical Machine Learning on Databricks. Seamlessly transition ML models and MLOps on Databricks
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Cracking the Data Engineering Interview. Land your dream job with the help of resume-building tips, over 100 mock questions, and a unique portfolio
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Alteryx Designer Cookbook. Over 60 recipes to transform your data into insights and take your productivity to a new level
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Synthetic Data for Machine Learning. Revolutionize your approach to machine learning with this comprehensive conceptual guide
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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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Building ETL Pipelines with Python. Create and deploy enterprise-ready ETL pipelines by employing modern methods
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Modern Data Architectures with Python. A practical guide to building and deploying data pipelines, data warehouses, and data lakes with Python
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Practical Data Quality. Learn practical, real-world strategies to transform the quality of data in your organization
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TensorFlow Developer Certificate Guide. Efficiently tackle deep learning and ML problems to ace the Developer Certificate exam
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Quantum Computing Algorithms. Discover how a little math goes a long way
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Learning Data Science
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Microsoft Power BI. Jak modelować i wizualizować dane oraz budować narracje cyfrowe. Wydanie III
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Przetwarzanie języka naturalnego w praktyce. Przewodnik po budowie rzeczywistych systemów NLP
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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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AI & Data Literacy. Empowering Citizens of Data Science
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Data Curious
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Data Engineering with dbt. A practical guide to building a cloud-based, pragmatic, and dependable data platform with SQL
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Enhancing Deep Learning with Bayesian Inference. Create more powerful, robust deep learning systems with Bayesian deep learning in Python
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Geospatial Data Analytics on AWS. Discover how to manage and analyze geospatial data in the cloud
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Natural Language Understanding with Python. Combine natural language technology, deep learning, and large language models to create human-like language comprehension in computer systems
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Zaufanie do systemów sztucznej inteligencji
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Embedded Analytics
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Streaming Data Mesh
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Data Augmentation with Python. Enhance deep learning accuracy with data augmentation methods for image, text, audio, and tabular data
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Building an Event-Driven Data Mesh
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Computer Vision on AWS. Build and deploy real-world CV solutions with Amazon Rekognition, Lookout for Vision, and SageMaker
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Analityka biznesowa wspomagana sztuczną inteligencją. Ulepszanie prognoz i podejmowania decyzji za pomocą uczenia maszynowego
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Machine Learning in Microservices. Productionizing microservices architecture for machine learning solutions
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The Kaggle Workbook. Self-learning exercises and valuable insights for Kaggle data science competitions
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The Enterprise Data Catalog
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Spark. Błyskawiczna analiza danych. Wydanie II
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Uczenie maszynowe. Elementy matematyki w analizie danych
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Modelowanie danych z Power BI dla ekspertów analityki. Jak w pełni wykorzystać możliwości Power BI
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Practicing Trustworthy Machine Learning
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The Art of Data-Driven Business. Transform your organization into a data-driven one with the power of Python machine learning
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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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Neural Search - From Prototype to Production with Jina. Build deep learning–powered search systems that you can deploy and manage with ease
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Scalable Data Architecture with Java. Build efficient enterprise-grade data architecting solutions using Java
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Data Quality Fundamentals
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Serverless ETL and Analytics with AWS Glue. Your comprehensive reference guide to learning about AWS Glue and its features
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SQL for Data Analytics. Harness the power of SQL to extract insights from data - Third Edition
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Inżynieria danych na platformie AWS. Jak tworzyć kompletne potoki uczenia maszynowego
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Głębokie uczenie. Wprowadzenie
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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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Machine Learning on Kubernetes. A practical handbook for building and using a complete open source machine learning platform on Kubernetes
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Data Democratization with Domo. Bring together every component of your business to make better data-driven decisions using Domo
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The Pandas Workshop. A comprehensive guide to using Python for data analysis with real-world case studies
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Excel 2021 i Microsoft 365. Przetwarzanie danych za pomocą tabel przestawnych
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AI-Powered Business Intelligence
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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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Fundamentals of Deep Learning. 2nd Edition
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Microsoft Power BI Performance Best Practices. A comprehensive guide to building consistently fast Power BI solutions
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The Kaggle Book. Data analysis and machine learning for competitive data science
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Automated Machine Learning on AWS. Fast-track the development of your production-ready machine learning applications the AWS way
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Getting Started with Elastic Stack 8.0. Run powerful and scalable data platforms to search, observe, and secure your organization
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Analiza danych behawioralnych przy użyciu języków R i Python
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Machine Learning with PyTorch and Scikit-Learn. Develop machine learning and deep learning models with Python
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AI-Powered Commerce. Building the products and services of the future with Commerce.AI
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Digital Transformation and Modernization with IBM API Connect. A practical guide to developing, deploying, and managing high-performance and secure hybrid-cloud APIs
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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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Agile Machine Learning with DataRobot. Automate each step of the machine learning life cycle, from understanding problems to delivering value
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Optimizing Databricks Workloads. Harness the power of Apache Spark in Azure and maximize the performance of modern big data workloads
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Machine Learning for Financial Risk Management with Python
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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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Uczenie głębokie i sztuczna inteligencja. Interaktywny przewodnik ilustrowany
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Machine Learning for Time-Series with Python. Forecast, predict, and detect anomalies with state-of-the-art machine learning methods
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Data Engineering with Apache Spark, Delta Lake, and Lakehouse. Create scalable pipelines that ingest, curate, and aggregate complex data in a timely and secure way
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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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Practical Weak Supervision
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Data Science for Marketing Analytics. A practical guide to forming a killer marketing strategy through data analysis with Python - 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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Software Architecture Patterns for Serverless Systems. Architecting for innovation with events, autonomous services, and micro frontends
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Wzorce projektowe uczenia maszynowego. Rozwiązania typowych problemów dotyczących przygotowania danych, konstruowania modeli i MLOps
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Graph Machine Learning. Take graph data to the next level by applying machine learning techniques and algorithms
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Statystyka praktyczna w data science. 50 kluczowych zagadnień w językach R i Python. Wydanie II
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97 Things Every Data Engineer Should Know
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Expert Data Modeling with Power BI. Get the best out of Power BI by building optimized data models for reporting and business needs
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Dane grafowe w praktyce. Jak technologie grafowe ułatwiają rozwiązywanie złożonych problemów
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Machine Learning with the Elastic Stack. Gain valuable insights from your data with Elastic Stack's machine learning features - Second Edition
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Mastering Tableau 2021. Implement advanced business intelligence techniques and analytics with Tableau - Third Edition
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Machine Learning for Time-Series with Python. Use Python to forecast, predict, and detect anomalies with state-of-the-art machine learning methods - Second Edition
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Applied Deep Learning on Graphs. Leveraging Graph Data to Generate Impact Using Specialized Deep Learning Architectures
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Becoming a Data Analyst. A beginner's guide to kickstarting your data analysis journey
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Learn Quantum Computing with Python and IBM Quantum. Write your own practical quantum programs with Python - Second Edition
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Generative AI Engineering, 1E. Build apps with transformer and diffusion-based large and foundational models
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Data Analysis with Polars. Get up and running with Polars to perform effective data analysis in Rust