Miguel Angel Garcia, Barry Harmsen, Stephen Redmond, Karl Pover - książki
Tytuły autora: dostępne w księgarni Ebookpoint
-
Getting Started with DuckDB. A practical guide for accelerating your data science, data analytics, and data engineering workflows
-
Augmented Analytics
-
Data Governance Handbook. A practical approach to building trust in data
-
Predictive Analytics for the Modern Enterprise
-
Data Analytics for Marketing. A practical guide to analyzing marketing data using Python
-
Fundamentals of Analytics Engineering. An introduction to building end-to-end analytics solutions
-
The Definitive Guide to Data Integration. Unlock the power of data integration to efficiently manage, transform, and analyze data
-
The Definitive Guide to Power Query (M). Mastering complex data transformation with Power Query
-
Building Interactive Dashboards in Microsoft 365 Excel. Harness the new features and formulae in M365 Excel to create dynamic, automated dashboards
-
Data-Centric Machine Learning with Python. The ultimate guide to engineering and deploying high-quality models based on good data
-
Learn Microsoft Fabric. A practical guide to performing data analytics in the era of artificial intelligence
-
Data Engineering with Scala and Spark. Build streaming and batch pipelines that process massive amounts of data using Scala
-
Developing Kaggle Notebooks. Pave your way to becoming a Kaggle Notebooks Grandmaster
-
Data Modeling with Microsoft Excel. Model and analyze data using Power Pivot, DAX, and Cube functions
-
Vector Search for Practitioners with Elastic. A toolkit for building NLP solutions for search, observability, and security using vector search
-
Cracking the Data Engineering Interview. Land your dream job with the help of resume-building tips, over 100 mock questions, and a unique portfolio
-
Alteryx Designer Cookbook. Over 60 recipes to transform your data into insights and take your productivity to a new level
-
Building ETL Pipelines with Python. Create and deploy enterprise-ready ETL pipelines by employing modern methods
-
Practical Data Quality. Learn practical, real-world strategies to transform the quality of data in your organization
-
Learning Data Science
-
Microsoft Power BI. Jak modelować i wizualizować dane oraz budować narracje cyfrowe. Wydanie III
-
AI & Data Literacy. Empowering Citizens of Data Science
-
Data Curious
-
Data Engineering with dbt. A practical guide to building a cloud-based, pragmatic, and dependable data platform with SQL
-
Enhancing Deep Learning with Bayesian Inference. Create more powerful, robust deep learning systems with Bayesian deep learning in Python
-
Geospatial Data Analytics on AWS. Discover how to manage and analyze geospatial data in the cloud
-
Natural Language Understanding with Python. Combine natural language technology, deep learning, and large language models to create human-like language comprehension in computer systems
-
Embedded Analytics
-
Streaming Data Mesh
-
Building an Event-Driven Data Mesh
-
Analityka biznesowa wspomagana sztuczną inteligencją. Ulepszanie prognoz i podejmowania decyzji za pomocą uczenia maszynowego
-
Machine Learning in Microservices. Productionizing microservices architecture for machine learning solutions
-
The Enterprise Data Catalog
-
Spark. Błyskawiczna analiza danych. Wydanie II
-
The Art of Data-Driven Business. Transform your organization into a data-driven one with the power of Python machine learning
-
Microsoft Power BI Quick Start Guide. The ultimate beginner's guide to data modeling, visualization, digital storytelling, and more - Third Edition
-
Data Quality Engineering in Financial Services
-
Neural Search - From Prototype to Production with Jina. Build deep learning–powered search systems that you can deploy and manage with ease
-
Scalable Data Architecture with Java. Build efficient enterprise-grade data architecting solutions using Java
-
Data Quality Fundamentals
-
Serverless ETL and Analytics with AWS Glue. Your comprehensive reference guide to learning about AWS Glue and its features
-
SQL for Data Analytics. Harness the power of SQL to extract insights from data - Third Edition
-
Data Democratization with Domo. Bring together every component of your business to make better data-driven decisions using Domo
-
The Pandas Workshop. A comprehensive guide to using Python for data analysis with real-world case studies
-
Excel 2021 i Microsoft 365. Przetwarzanie danych za pomocą tabel przestawnych
-
AI-Powered Business Intelligence
-
Microsoft Power BI. Jak modelować i wizualizować dane oraz budować narracje cyfrowe. Wydanie II
-
Getting Started with Elastic Stack 8.0. Run powerful and scalable data platforms to search, observe, and secure your organization
-
Analiza danych behawioralnych przy użyciu języków R i Python
-
AI-Powered Commerce. Building the products and services of the future with Commerce.AI
-
Digital Transformation and Modernization with IBM API Connect. A practical guide to developing, deploying, and managing high-performance and secure hybrid-cloud APIs
-
Optimizing Databricks Workloads. Harness the power of Apache Spark in Azure and maximize the performance of modern big data workloads
-
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
-
Microsoft Power BI Cookbook. Gain expertise in Power BI with over 90 hands-on recipes, tips, and use cases - Second Edition
-
Data Science for Marketing Analytics. A practical guide to forming a killer marketing strategy through data analysis with Python - Second Edition
-
Software Architecture Patterns for Serverless Systems. Architecting for innovation with events, autonomous services, and micro frontends
-
Statystyka praktyczna w data science. 50 kluczowych zagadnień w językach R i Python. Wydanie II
-
97 Things Every Data Engineer Should Know
-
Expert Data Modeling with Power BI. Get the best out of Power BI by building optimized data models for reporting and business needs
-
Dane grafowe w praktyce. Jak technologie grafowe ułatwiają rozwiązywanie złożonych problemów
-
Mastering Tableau 2021. Implement advanced business intelligence techniques and analytics with Tableau - Third Edition
-
Distributed Data Systems with Azure Databricks. Create, deploy, and manage enterprise data pipelines
-
Automated Machine Learning with AutoKeras. Deep learning made accessible for everyone with just few lines of coding
-
Interactive Dashboards and Data Apps with Plotly and Dash. Harness the power of a fully fledged frontend web framework in Python – no JavaScript required
-
Skazany na sukces. Kariera w Data Science
-
Scalable Data Streaming with Amazon Kinesis. Design and secure highly available, cost-effective data streaming applications with Amazon Kinesis
-
Managing Microsoft Teams: MS-700 Exam Guide. Configure and manage Microsoft Teams workloads and achieve Microsoft 365 certification with ease
-
Odsłaniamy SQL Server 2019: Klastry Big Data i uczenie maszynowe
-
The Economics of Data, Analytics, and Digital Transformation. The theorems, laws, and empowerments to guide your organization’s digital transformation
-
Corporate Learning with Moodle Workplace. Explore concepts, implementation, and strategies for adopting Moodle Workplace in your organization
-
Microsoft Excel 2013 Budowanie modeli danych przy użyciu PowerPivot
-
Microsoft SQL Server 2012 Analysis Services: Model tabelaryczny BISM
-
Tableau Desktop Cookbook
-
Microsoft Power BI Quick Start Guide. Bring your data to life through data modeling, visualization, digital storytelling, and more - Second Edition
-
Deep Learning for Beginners. A beginner's guide to getting up and running with deep learning from scratch using Python
-
The Data Science Workshop. Learn how you can build machine learning models and create your own real-world data science projects - Second Edition
-
Power BI i Power Pivot dla Excela. Analiza danych
-
The Deep Learning Workshop. Learn the skills you need to develop your own next-generation deep learning models with TensorFlow and Keras
-
The Data Analysis Workshop. Solve business problems with state-of-the-art data analysis models, developing expert data analysis skills along the way
-
The Data Wrangling Workshop. Create your own actionable insights using data from multiple raw sources - Second Edition
-
The Deep Learning with Keras Workshop. Learn how to define and train neural network models with just a few lines of code
-
The Data Visualization Workshop. A self-paced, practical approach to transforming your complex data into compelling, captivating graphics
-
Building Analytics Teams. Harnessing analytics and artificial intelligence for business improvement
-
Hands-On Python Deep Learning for the Web. Integrating neural network architectures to build smart web apps with Flask, Django, and TensorFlow
-
Kompletny przewodnik po DAX, wyd. 2 rozszerzone. Analiza biznesowa przy użyciu Microsoft Power BI, SQL Server Analysis Services i Excel
-
Mobile Deep Learning with TensorFlow Lite, ML Kit and Flutter. Build scalable real-world projects to implement end-to-end neural networks on Android and iOS
-
The Practitioner's Guide to Graph Data. Applying Graph Thinking and Graph Technologies to Solve Complex Problems
-
The Applied SQL Data Analytics Workshop. Develop your practical skills and prepare to become a professional data analyst - Second Edition
-
The Data Science Workshop. A New, Interactive Approach to Learning Data Science
-
Tableau Desktop Certified Associate: Exam Guide. Develop your Tableau skills and prepare for Tableau certification with tips from industry experts
-
Microsoft Excel 2019 Przetwarzanie danych za pomocą tabel przestawnych
-
Managing Data Science. Effective strategies to manage data science projects and build a sustainable team
-
Learn Algorithmic Trading. Build and deploy algorithmic trading systems and strategies using Python and advanced data analysis
-
Hands-On Artificial Intelligence on Amazon Web Services. Decrease the time to market for AI and ML applications with the power of AWS
-
Get Your Hands Dirty on Clean Architecture. A hands-on guide to creating clean web applications with code examples in Java
-
Binary Analysis Cookbook. Actionable recipes for disassembling and analyzing binaries for security risks
-
SQL for Data Analytics. Perform fast and efficient data analysis with the power of SQL
-
Cloud Native. Using Containers, Functions, and Data to Build Next-Generation Applications
-
Hands-On Deep Learning for IoT. Train neural network models to develop intelligent IoT applications
-
Geospatial Data Science Quick Start Guide. Effective techniques for performing smarter geospatial analysis using location intelligence
-
Data Science for Marketing Analytics. Achieve your marketing goals with the data analytics power of Python
-
Hands-On Big Data Analytics with PySpark. Analyze large datasets and discover techniques for testing, immunizing, and parallelizing Spark jobs
-
Applied Unsupervised Learning with R. Uncover hidden relationships and patterns with k-means clustering, hierarchical clustering, and PCA
-
Hands-On Dashboard Development with QlikView. Practical guide to creating interactive and user-friendly business intelligence dashboards
-
Data Wrangling with Python. Creating actionable data from raw sources
-
Hands-On Business Intelligence with Qlik Sense. Implement self-service data analytics with insights and guidance from Qlik Sense experts
-
Mastering Tableau 2019.1. An expert guide to implementing advanced business intelligence and analytics with Tableau 2019.1 - Second Edition
-
Wprowadzenie do systemów baz danych. Wydanie VII
-
Advanced MySQL 8. Discover the full potential of MySQL and ensure high performance of your database
-
Hands-On Data Science with the Command Line. Automate everyday data science tasks using command-line tools
-
Machine Learning with the Elastic Stack. Expert techniques to integrate machine learning with distributed search and analytics
-
Tableau 2019.x Cookbook. Over 115 recipes to build end-to-end analytical solutions using Tableau
-
Storytelling danych. Poradnik wizualizacji danych dla profesjonalistów
-
Blockchain Quick Start Guide. A beginner's guide to developing enterprise-grade decentralized applications
-
QlikView: Advanced Data Visualization. Discover deeper insights with Qlikview by building your own rich analytical applications from scratch
-
Becoming a Data Analyst. A beginner's guide to kickstarting your data analysis journey
-
Generative AI Engineering, 1E. Build apps with transformer and diffusion-based large and foundational models
-
Data Analysis with Polars. Get up and running with Polars to perform effective data analysis with Rust
-
Microsoft Power BI Cookbook. Turn data into strategic assets with updated techniques, features, use cases and best practices - Third Edition
-
Learning Kibana 7. Build powerful Elastic dashboards with Kibana's data visualization capabilities - Second Edition