Radhika Datar, Harish Garg - książki
Tytuły autora: dostępne w księgarni Ebookpoint
-
Uczenie maszynowe w Pythonie. Deep learning i machine learning
-
Practical Lakehouse Architecture
-
Getting Started with DuckDB. A practical guide for accelerating your data science, data analytics, and data engineering workflows
-
Data Engineering with Databricks Cookbook. Build effective data and AI solutions using Apache Spark, Databricks, and Delta Lake
-
Python Data Cleaning Cookbook. Prepare your data for analysis with pandas, NumPy, Matplotlib, scikit-learn, and OpenAI - Second Edition
-
The Ultimate Guide to Snowpark. Design and deploy Snowpark with Python for efficient data workloads
-
Extending Excel with Python and R. Unlock the potential of analytics languages for advanced data manipulation and visualization
-
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
-
Uczenie maszynowe: Scikit-Learn, Keras i TensorFlow. Szczegółowy poradnik
-
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
-
Kibana 8.x - A Quick Start Guide to Data Analysis. Learn about data exploration, visualization, and dashboard building with Kibana
-
Specyfikacja wymagań oprogramowania. Kluczowe praktyki analizy biznesowej
-
Data Observability for Data Engineering. Proactive strategies for ensuring data accuracy and addressing broken data pipelines
-
The Deep Learning Architect's Handbook. Build and deploy production-ready DL solutions leveraging the latest Python techniques
-
Web Data Mining z użyciem języka Python. Odkrywaj i wyodrębniaj informacje ze stron internetowych za pomocą języka Python
-
Data Exploration and Preparation with BigQuery. A practical guide to cleaning, transforming, and analyzing data for business insights
-
Cracking the Data Engineering Interview. Land your dream job with the help of resume-building tips, over 100 mock questions, and a unique portfolio
-
Google Analytics od podstaw. Analiza wpływu biznesowego i wyznaczanie trendów
-
Amazon Redshift: The Definitive Guide
-
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
-
Microsoft Power BI. Jak modelować i wizualizować dane oraz budować narracje cyfrowe. Wydanie III
-
AI w Biznesie: Praktyczny Przewodnik Stosowania Sztucznej Inteligencji w Różnych Branżach
-
Data Wrangling on AWS. Clean and organize complex data for analysis
-
Data Wrangling with SQL. A hands-on guide to manipulating, wrangling, and engineering data using SQL
-
Microsoft Power BI dla bystrzaków
-
Marketing i analityka biznesowa dla początkujących. Poznaj najważniejsze narzędzia i wykorzystaj ich możliwości
-
Python w analizie danych. Przetwarzanie danych za pomocą pakietów pandas i NumPy oraz środowiska Jupyter. Wydanie III
-
Driving Data Quality with Data Contracts. A comprehensive guide to building reliable, trusted, and effective data platforms
-
Graph Data Modeling in Python. A practical guide to curating, analyzing, and modeling data with graphs
-
Data Modeling with Snowflake. A practical guide to accelerating Snowflake development using universal data modeling techniques
-
Siatka danych. Nowoczesna koncepcja samoobsługowej infrastruktury danych
-
Wizualizacja danych. Pulpity nawigacyjne i raporty w Excelu
-
Zaawansowana analiza danych w PySpark. Metody przetwarzania informacji na szeroką skalę z wykorzystaniem Pythona i systemu Spark
-
Robo-Advisor with Python. A hands-on guide to building and operating your own Robo-advisor
-
DAX i Power BI w analizie danych. Tworzenie zaawansowanych i efektywnych analiz dla biznesu
-
Spark. Błyskawiczna analiza danych. Wydanie II
-
Tomographic imaging in environmental, industrial and medical applications
-
Microsoft Power BI Quick Start Guide. The ultimate beginner's guide to data modeling, visualization, digital storytelling, and more - Third Edition
-
Machine Learning Techniques for Text. Apply modern techniques with Python for text processing, dimensionality reduction, classification, and evaluation
-
Dziennikarstwo danych i data storytelling
-
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
-
Cyfrowe Państwo. Uwarunkowania i perspektywy
-
Data Cleaning and Exploration with Machine Learning. Get to grips with machine learning techniques to achieve sparkling-clean data quickly
-
Feature Store for Machine Learning. Curate, discover, share and serve ML features at scale
-
The Pandas Workshop. A comprehensive guide to using Python for data analysis with real-world case studies
-
Microsoft Power BI. Jak modelować i wizualizować dane oraz budować narracje cyfrowe. Wydanie II
-
Deep Learning with PyTorch Lightning. Swiftly build high-performance Artificial Intelligence (AI) models using Python
-
The Tableau Workshop. A practical guide to the art of data visualization with Tableau
-
Simplify Big Data Analytics with Amazon EMR. A beginner’s guide to learning and implementing Amazon EMR for building data analytics solutions
-
Getting Started with Elastic Stack 8.0. Run powerful and scalable data platforms to search, observe, and secure your organization
-
Reproducible Data Science with Pachyderm. Learn how to build version-controlled, end-to-end data pipelines using Pachyderm 2.0
-
Data Mesh
-
AI-Powered Commerce. Building the products and services of the future with Commerce.AI
-
Extreme DAX. Take your Power BI and Microsoft data analytics skills to the next level
-
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
-
Digital Transformation with Dataverse for Teams. Become a citizen developer and lead the digital transformation wave with Microsoft Teams and Power Platform
-
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
-
LaTeX Beginner's Guide. Create visually appealing texts, articles, and books for business and science using LaTeX - Second Edition
-
Microsoft Power BI Cookbook. Gain expertise in Power BI with over 90 hands-on recipes, tips, and use cases - Second Edition
-
Up and Running with Affinity Designer. A practical, easy-to-follow guide to get up to speed with the powerful features of Affinity Designer 1.10
-
Deep Learning with fastai Cookbook. Leverage the easy-to-use fastai framework to unlock the power of deep learning
-
3D Graphics Rendering Cookbook. A comprehensive guide to exploring rendering algorithms in modern OpenGL and Vulkan
-
Tableau Strategies
-
Amazon Redshift Cookbook. Recipes for building modern data warehousing solutions
-
Mastering spaCy. An end-to-end practical guide to implementing NLP applications using the Python ecosystem
-
Limitless Analytics with Azure Synapse. An end-to-end analytics service for data processing, management, and ingestion for BI and ML
-
Statystyka praktyczna w data science. 50 kluczowych zagadnień w językach R i Python. Wydanie II
-
Expert Data Modeling with Power BI. Get the best out of Power BI by building optimized data models for reporting and business needs
-
Mastering Tableau 2021. Implement advanced business intelligence techniques and analytics with Tableau - Third Edition
-
Hands-On Data Analysis with Pandas. A Python data science handbook for data collection, wrangling, analysis, and visualization - Second Edition
-
Hands-On Financial Trading with Python. A practical guide to using Zipline and other Python libraries for backtesting trading strategies
-
Scalable Data Streaming with Amazon Kinesis. Design and secure highly available, cost-effective data streaming applications with Amazon Kinesis
-
Effortless App Development with Oracle Visual Builder. Boost productivity by building web and mobile applications efficiently using the drag-and-drop approach
-
Hands-On Data Visualization
-
Hurtownie danych. Od przetwarzania analitycznego do raportowania. Wydanie II
-
Kluczowe kompetencje specjalisty danych
-
Wykorzystanie sztucznych sieci neuronowych
-
Python Data Cleaning Cookbook. Modern techniques and Python tools to detect and remove dirty data and extract key insights
-
Analiza danych w zarządzaniu projektami
-
The Economics of Data, Analytics, and Digital Transformation. The theorems, laws, and empowerments to guide your organization’s digital transformation
-
Codeless Deep Learning with KNIME. Build, train, and deploy various deep neural network architectures using KNIME Analytics Platform
-
Learn TensorFlow Enterprise. Build, manage, and scale machine learning workloads seamlessly using Google's TensorFlow Enterprise
-
Microsoft Power BI Quick Start Guide. Bring your data to life through data modeling, visualization, digital storytelling, and more - Second Edition
-
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 Computer Vision Workshop. Develop the skills you need to use computer vision algorithms in your own artificial intelligence projects
-
Building Analytics Teams. Harnessing analytics and artificial intelligence for business improvement
-
Practical Synthetic Data Generation. Balancing Privacy and the Broad Availability of Data
-
Hands-On Python Deep Learning for the Web. Integrating neural network architectures to build smart web apps with Flask, Django, and TensorFlow
-
Hands-On Exploratory Data Analysis with Python. Perform EDA techniques to understand, summarize, and investigate your data
-
The Applied SQL Data Analytics Workshop. Develop your practical skills and prepare to become a professional data analyst - Second Edition
-
Deep Learning with R Cookbook. Over 45 unique recipes to delve into neural network techniques using R 3.5.x
-
Podstawy wizualizacji danych. Zasady tworzenia atrakcyjnych wykresów
-
Deep Learning with TensorFlow 2 and Keras. Regression, ConvNets, GANs, RNNs, NLP, and more with TensorFlow 2 and the Keras API - Second Edition
-
Tableau Desktop Certified Associate: Exam Guide. Develop your Tableau skills and prepare for Tableau certification with tips from industry experts
-
Managing Data Science. Effective strategies to manage data science projects and build a sustainable team
-
Korporacyjne jezioro danych. Wykorzystaj potencjał big data w swojej organizacji
-
Extreme C. Taking you to the limit in Concurrency, OOP, and the most advanced capabilities of C
-
Mastering pandas. A complete guide to pandas, from installation to advanced data analysis techniques - Second Edition
-
arc42 by Example. Software architecture documentation in practice
-
Learn Power BI. A beginner's guide to developing interactive business intelligence solutions using Microsoft Power BI
-
SQL for Data Analytics. Perform fast and efficient data analysis with the power of SQL
-
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
-
Hands-On Exploratory Data Analysis with R. Become an expert in exploratory data analysis using R packages
-
Polars Cookbook. Over 60 practical recipes to transform, manipulate, and analyze your data using Python Polars 1.x
-
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
-
Microsoft Power BI Cookbook. Convert raw data into business insights with updated techniques, use cases, and best practices - Third Edition
-
Data Management Strategy at Microsoft. Best practices from a tech giant's decade-long data transformation journey
-
Analiza statystyczna z IBM SPSS Statistics
-
Cloud Analytics with Microsoft Azure. Build modern data warehouses with the combined power of analytics and Azure