Stefan Jansen - książki
Tytuły autora: dostępne w księgarni Ebookpoint
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Sztuczna Inteligencja i Uczenie Maszynowe: Kompletny Przewodnik do Budowy Własnych Rozwiązań AI
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Tableau Certified Data Analyst Certification Guide. Ace the Tableau Data Analyst certification exam with expert guidance and practice material
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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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Data Modeling with Microsoft Power BI
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The Ultimate Guide to Snowpark. Design and deploy Snowpark with Python for efficient data workloads
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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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Data Quality in the Age of AI. Building a foundation for AI strategy and data culture
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Dylemat sztucznej inteligencji. 7 zasad odpowiedzialnego tworzenia technologii
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Data Engineering with Google Cloud Platform. A guide to leveling up as a data engineer by building a scalable data platform with Google Cloud - Second Edition
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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 Power Query (M). Mastering complex data transformation with Power Query
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Artificial Intelligence with Microsoft Power BI
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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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Data-Centric Machine Learning with Python. The ultimate guide to engineering and deploying high-quality models based on good data
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Deciphering Data Architectures
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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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Data Labeling in Machine Learning with Python. Explore modern ways to prepare labeled data for training and fine-tuning ML and generative AI models
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Managing Data Integrity for Finance. Discover practical data quality management strategies for finance analysts and data professionals
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Automating Data Quality Monitoring
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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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Practical Guide to Applied Conformal Prediction in Python. Learn and apply the best uncertainty frameworks to your industry applications
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Web Data Mining z użyciem języka Python. Odkrywaj i wyodrębniaj informacje ze stron internetowych za pomocą języka Python
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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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Power BI i sztuczna inteligencja. Jak w pełni wykorzystać funkcje AI dostępne w Power BI
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Analityk danych. Przewodnik po data science, statystyce i uczeniu maszynowym
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Tworzenie rozwiązań za pomocą Microsoft Power Platform. Rozwiązywanie codziennych problemów w przedsiębiorstwie
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Amazon Redshift: The Definitive Guide
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Building ETL Pipelines with Python. Create and deploy enterprise-ready ETL pipelines by employing modern methods
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Learning Data Science
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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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Microsoft Power BI dla bystrzaków
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Poznaj Tableau 2022. Wizualizacja danych, interaktywna analiza danych i umiejętność data storytellingu. Wydanie V
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Driving Data Quality with Data Contracts. A comprehensive guide to building reliable, trusted, and effective data platforms
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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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Graph Data Modeling in Python. A practical guide to curating, analyzing, and modeling data with graphs
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Inżynieria danych w praktyce. Kluczowe koncepcje i najlepsze technologie
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Zaufanie do systemów sztucznej inteligencji
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Potoki danych. Leksykon kieszonkowy. Przenoszenie i przetwarzanie danych na potrzeby ich analizy
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Embedded Analytics
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Machine Learning for High-Risk Applications
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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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Poznaj Microsoft Power BI. Przekształcanie danych we wnioski
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Zaawansowana analiza danych w PySpark. Metody przetwarzania informacji na szeroką skalę z wykorzystaniem Pythona i systemu Spark
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Applied Geospatial Data Science with Python. Leverage geospatial data analysis and modeling to find unique solutions to environmental problems
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Spark. Błyskawiczna analiza danych. Wydanie II
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Practicing Trustworthy Machine Learning
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Machine Learning Model Serving Patterns and Best Practices. A definitive guide to deploying, monitoring, and providing accessibility to ML models in production
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Transforming Healthcare with DevOps. A practical DevOps4Care guide to embracing the complexity of digital transformation
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Modern Time Series Forecasting with Python. Explore industry-ready time series forecasting using modern machine learning and deep learning
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Applied Machine Learning and AI for Engineers
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Quantum Machine Learning and Optimisation in Finance. On the Road to Quantum Advantage
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Deep Learning with TensorFlow and Keras. Build and deploy supervised, unsupervised, deep, and reinforcement learning models - Third Edition
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Scalable Data Architecture with Java. Build efficient enterprise-grade data architecting solutions using Java
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Learning Microsoft Power BI
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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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Simplifying Android Development with Coroutines and Flows. Learn how to use Kotlin coroutines and the flow API to handle data streams asynchronously in your Android app
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Tidy Modeling with R
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Feature Store for Machine Learning. Curate, discover, share and serve ML features at scale
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Fundamentals of Data Engineering
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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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Fundamentals of Deep Learning. 2nd Edition
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Artificial Intelligence with Power BI. Take your data analytics skills to the next level by leveraging the AI capabilities in Power BI
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Democratizing Artificial Intelligence with UiPath. Expand automation in your organization to achieve operational efficiency and high performance
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Natural Language Processing with Flair. A practical guide to understanding and solving NLP problems with Flair
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The Tableau Workshop. A practical guide to the art of data visualization with Tableau
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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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Data Engineering with Google Cloud Platform. A practical guide to operationalizing scalable data analytics systems on GCP
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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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Scalable Data Analytics with Azure Data Explorer. Modern ways to query, analyze, and perform real-time data analysis on large volumes of data
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Machine Learning with PyTorch and Scikit-Learn. Develop machine learning and deep learning models with Python
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Hands-On Data Preprocessing in Python. Learn how to effectively prepare data for successful data analytics
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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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Agile Machine Learning with DataRobot. Automate each step of the machine learning life cycle, from understanding problems to delivering value
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Learn Amazon SageMaker. A guide to building, training, and deploying machine learning models for developers and data scientists - Second Edition
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Uczenie głębokie i sztuczna inteligencja. Interaktywny przewodnik ilustrowany
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Machine Learning with Amazon SageMaker Cookbook. 80 proven recipes for data scientists and developers to perform machine learning experiments and deployments
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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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Power Query Cookbook. Use effective and powerful queries in Power BI Desktop and Dataflows to prepare and transform your data
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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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Data Analytics Made Easy. Analyze and present data to make informed decisions without writing any code
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Software Architecture Patterns for Serverless Systems. Architecting for innovation with events, autonomous services, and micro frontends
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Tableau Strategies
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Amazon Redshift Cookbook. Recipes for building modern data warehousing solutions
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Deep learning dla programistów. Budowanie aplikacji AI za pomocą fastai i PyTorch
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PyTorch Pocket Reference
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Quantum Computing with Silq Programming. Get up and running with quantum computing with the simplicity of this new high-level programming language
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Hands-On Data Analysis with Pandas. A Python data science handbook for data collection, wrangling, analysis, and visualization - Second Edition
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Hands-On Financial Trading with Python. A practical guide to using Zipline and other Python libraries for backtesting trading strategies
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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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Scalable Data Streaming with Amazon Kinesis. Design and secure highly available, cost-effective data streaming applications with Amazon Kinesis
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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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Hands-On Data Visualization
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Mastering PyTorch. Build powerful neural network architectures using advanced PyTorch 1.x features
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Data Pipelines Pocket Reference
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Python. Machine learning i deep learning. Biblioteki scikit-learn i TensorFlow 2. Wydanie III
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Język R i analiza danych w praktyce. Wydanie II
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Kubeflow Operations Guide
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Microsoft Power Platform Functional Consultant: PL-200 Exam Guide. Learn how to customize and configure Microsoft Power Platform and prepare for the PL-200 exam
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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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Applied Deep Learning and Computer Vision for Self-Driving Cars. Build autonomous vehicles using deep neural networks and behavior-cloning techniques
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Machine Learning for Algorithmic Trading. Predictive models to extract signals from market and alternative data for systematic trading strategies with Python - 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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Causal Inference in R. Decipher complex relationships with advanced R techniques for data-driven decision making
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Modern Time Series Forecasting with Python. Industry-ready machine learning and deep learning time series analysis with PyTorch and pandas - Second Edition
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Data Analysis with Polars. Get up and running with Polars to perform effective data analysis with Rust
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Python for Algorithmic Trading Cookbook. Recipes for designing, building, and deploying algorithmic trading strategies with Python
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Data Science for Decision Makers. Enhance your leadership skills with data science and AI expertise
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Data Management Strategy at Microsoft. Best practices from a tech giant's decade-long data transformation journey
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Analiza statystyczna z IBM SPSS Statistics
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Technologie informatyczne a prawo. Prolegomena