W dobie cyfrowej transformacji, Big Data stało się jednym z najważniejszych tematów w świecie informatyki i biznesu. W Helion rozumiemy potrzebę poszerzenia wiedzy na ten temat, dlatego oferujemy Ci szeroki wybór książek poświęconych tematyce Big Data. Nasze publikacje zapewniają solidne podstawy teoretyczne oraz praktyczne wskazówki, które są niezbędne do zrozumienia i wykorzystania potencjału “wielkich danych” w różnych dziedzinach.
Big Data
Książki, ebooki, audiobooki, kursy video z kategorii: Big Data dostępne w księgarni Helion
-
Hands-On Artificial Intelligence on Amazon Web Services. Decrease the time to market for AI and ML applications with the power of AWS
-
Hands-On Internet of Things with MQTT. Build connected IoT devices with Arduino and MQ Telemetry Transport (MQTT)
-
Developer, Advocate!. Conversations on turning a passion for talking about tech into a career
-
Hands-On SAS For Data Analysis. A practical guide to performing effective queries, data visualization, and reporting techniques
-
Hands-On Application Development with PyCharm. Accelerate your Python applications using practical coding techniques in PyCharm
-
Binary Analysis Cookbook. Actionable recipes for disassembling and analyzing binaries for security risks
-
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
-
Cloud Native. Using Containers, Functions, and Data to Build Next-Generation Applications
-
Big Data Analytics with Java. Data analysis, visualization & machine learning techniques
-
Hands-On Deep Learning with Go. A practical guide to building and implementing neural network models using Go
-
Hands-On Data Analysis with Pandas. Efficiently perform data collection, wrangling, analysis, and visualization using Python
-
Hands-On Deep Learning Algorithms with Python. Master deep learning algorithms with extensive math by implementing them using TensorFlow
-
Data Science i uczenie maszynowe
-
Mastering PostGIS. Modern ways to create, analyze, and implement spatial data
-
Hands-On Web Scraping with Python. Perform advanced scraping operations using various Python libraries and tools such as Selenium, Regex, and others
-
Hands-On Deep Learning for IoT. Train neural network models to develop intelligent IoT applications
-
R Cookbook. Proven Recipes for Data Analysis, Statistics, and Graphics. 2nd Edition
-
Zapytania w języku T-SQL w Microsoft SQL Server 2014 i SQL Server 2012
-
Kompletny przewodnik po DAX. Analiza biznesowa przy użyciu Microsoft Excel, SQL Server Analysis Services i Power BI
-
Hands-On Time Series Analysis with R. Perform time series analysis and forecasting using R
-
Hands-On Exploratory Data Analysis with R. Become an expert in exploratory data analysis using R packages
-
Geospatial Data Science Quick Start Guide. Effective techniques for performing smarter geospatial analysis using location intelligence
-
Hands-On Data Analysis with Scala. Perform data collection, processing, manipulation, and visualization with Scala
-
Hands-On Deep Learning Architectures with Python. Create deep neural networks to solve computational problems using TensorFlow and Keras
-
Hands-On Deep Learning for Games. Leverage the power of neural networks and reinforcement learning to build intelligent games
-
Mastering MongoDB 4.x. Expert techniques to run high-volume and fault-tolerant database solutions using MongoDB 4.x - Second Edition
-
TensorFlow Reinforcement Learning Quick Start Guide. Get up and running with training and deploying intelligent, self-learning agents using Python
-
Mobile Artificial Intelligence Projects. Develop seven projects on your smartphone using artificial intelligence and deep learning techniques
-
Natural Language Processing Fundamentals. Build intelligent applications that can interpret the human language to deliver impactful results
-
R Statistics Cookbook. Over 100 recipes for performing complex statistical operations with R 3.5
-
TensorFlow 2.0 Quick Start Guide. Get up to speed with the newly introduced features of TensorFlow 2.0
-
Hands-On Data Science for Marketing. Improve your marketing strategies with machine learning using Python and R
-
Machine Learning with R Quick Start Guide. A beginner's guide to implementing machine learning techniques from scratch using R 3.5
-
Hands-On Big Data Analytics with PySpark. Analyze large datasets and discover techniques for testing, immunizing, and parallelizing Spark jobs
-
Deep Learning with Microsoft Cognitive Toolkit Quick Start Guide. A practical guide to building neural networks using Microsoft's open source deep learning framework
-
Applied Unsupervised Learning with R. Uncover hidden relationships and patterns with k-means clustering, hierarchical clustering, and PCA
-
Learning Tableau 2019. Tools for Business Intelligence, data prep, and visual analytics - Third Edition
-
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 Unsupervised Learning with Python. Implement machine learning and deep learning models using Scikit-Learn, TensorFlow, and more
-
Mastering Tableau 2019.1. An expert guide to implementing advanced business intelligence and analytics with Tableau 2019.1 - Second Edition
-
Hands-On Business Intelligence with Qlik Sense. Implement self-service data analytics with insights and guidance from Qlik Sense experts
-
Learn Chart.js. Create interactive visualizations for the Web with Chart.js 2
-
Mastering Hadoop 3. Big data processing at scale to unlock unique business insights
-
SAP Business Intelligence Quick Start Guide. Actionable business insights from the SAP BusinessObjects BI platform
-
Hands-On Blockchain for Python Developers. Gain blockchain programming skills to build decentralized applications using Python
-
Ensemble Machine Learning Cookbook. Over 35 practical recipes to explore ensemble machine learning techniques using Python
-
Hands-On Deep Learning with Apache Spark. Build and deploy distributed deep learning applications on Apache Spark
-
Machine Learning with the Elastic Stack. Expert techniques to integrate machine learning with distributed search and analytics
-
Mastering Machine Learning with R. Advanced machine learning techniques for building smart applications with R 3.5 - Third Edition
-
Apache Spark Quick Start Guide. Quickly learn the art of writing efficient big data applications with Apache Spark
-
Generative Adversarial Networks Projects. Build next-generation generative models using TensorFlow and Keras
-
Hands-On Artificial Intelligence for IoT. Expert machine learning and deep learning techniques for developing smarter IoT systems
-
Machine Learning Quick Reference. Quick and essential machine learning hacks for training smart data models
-
Python Machine Learning Blueprints. Put your machine learning concepts to the test by developing real-world smart projects - Second Edition
-
Kibana 7 Quick Start Guide. Visualize your Elasticsearch data with ease
-
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
-
Intelligent Projects Using Python. 9 real-world AI projects leveraging machine learning and deep learning with TensorFlow and Keras
-
Tableau 2019.x Cookbook. Over 115 recipes to build end-to-end analytical solutions using Tableau
-
Go Web Scraping Quick Start Guide. Implement the power of Go to scrape and crawl data from the web
-
Blockchain for Business 2019. A user-friendly introduction to blockchain technology and its business applications
-
Python Deep Learning. Exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow - Second Edition
-
R Machine Learning Projects. Implement supervised, unsupervised, and reinforcement learning techniques using R 3.5
-
Generative Adversarial Networks Cookbook. Over 100 recipes to build generative models using Python, TensorFlow, and Keras
-
Hands-On Machine Learning for Algorithmic Trading. Design and implement investment strategies based on smart algorithms that learn from data using Python
-
Machine Learning for Mobile. Practical guide to building intelligent mobile applications powered by machine learning
-
Ripple Quick Start Guide. Get started with XRP and develop applications on Ripple's blockchain
-
Computer Vision Projects with OpenCV and Python 3. Six end-to-end projects built using machine learning with OpenCV, Python, and TensorFlow
-
Hands-On Predictive Analytics with Python. Master the complete predictive analytics process, from problem definition to model deployment
-
Apache Kafka Quick Start Guide. Leverage Apache Kafka 2.0 to simplify real-time data processing for distributed applications
-
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
-
Julia Programming Projects. Learn Julia 1.x by building apps for data analysis, visualization, machine learning, and the web
-
Bayesian Analysis with Python. Introduction to statistical modeling and probabilistic programming using PyMC3 and ArviZ - Second Edition
-
Principles of Data Science. Understand, analyze, and predict data using Machine Learning concepts and tools - Second Edition
-
Deep Learning with PyTorch Quick Start Guide. Learn to train and deploy neural network models in Python
-
Tableau 10 Complete Reference. Transform your business with rich data visualizations and interactive dashboards with Tableau 10
-
Apache Spark 2: Data Processing and Real-Time Analytics. Master complex big data processing, stream analytics, and machine learning with Apache Spark
-
Numerical Computing with Python. Harness the power of Python to analyze and find hidden patterns in the data
-
Microsoft Power BI Complete Reference. Bring your data to life with the powerful features of Microsoft Power BI
-
Apache Superset Quick Start Guide. Develop interactive visualizations by creating user-friendly dashboards
-
Practical Site Reliability Engineering. Automate the process of designing, developing, and delivering highly reliable apps and services with SRE
-
Hands-On Data Science with R. Techniques to perform data manipulation and mining to build smart analytical models using R
-
Natural Language Processing with Python Quick Start Guide. Going from a Python developer to an effective Natural Language Processing Engineer
-
TensorFlow Machine Learning Projects. Build 13 real-world projects with advanced numerical computations using the Python ecosystem
-
Hands-On Big Data Modeling. Effective database design techniques for data architects and business intelligence professionals
-
Recurrent Neural Networks with Python Quick Start Guide. Sequential learning and language modeling with TensorFlow
-
Hands-On Geospatial Analysis with R and QGIS. A beginner’s guide to manipulating, managing, and analyzing spatial data using R and QGIS 3.2.2
-
Blockchain By Example. A developer's guide to creating decentralized applications using Bitcoin, Ethereum, and Hyperledger
-
Apache Ignite Quick Start Guide. Distributed data caching and processing made easy
-
PostgreSQL 11 Server Side Programming Quick Start Guide. Effective database programming and interaction
-
Julia 1.0 Programming Cookbook. Over 100 numerical and distributed computing recipes for your daily data science work?ow
-
Hands-On Data Science with SQL Server 2017. Perform end-to-end data analysis to gain efficient data insight
-
Splunk 7.x Quick Start Guide. Gain business data insights from operational intelligence
-
Mastering Matplotlib 2.x. Effective Data Visualization techniques with Python
-
Hands-On Artificial Intelligence for Beginners. An introduction to AI concepts, algorithms, and their implementation
-
Getting Started with Haskell Data Analysis. Put your data analysis techniques to work and generate publication-ready visualizations
-
R Web Scraping Quick Start Guide. Techniques and tools to crawl and scrape data from websites
-
Applied Data Science with Python and Jupyter. Use powerful industry-standard tools to unlock new, actionable insights from your data
-
Python Fundamentals. A practical guide for learning Python, complete with real-world projects for you to explore
-
Data Science Algorithms in a Week. Top 7 algorithms for scientific computing, data analysis, and machine learning - Second Edition
-
Hands-On Machine Learning with Azure. Build powerful models with cognitive machine learning and artificial intelligence
-
Advanced Deep Learning with Keras. Apply deep learning techniques, autoencoders, GANs, variational autoencoders, deep reinforcement learning, policy gradients, and more
-
Apache Hadoop 3 Quick Start Guide. Learn about big data processing and analytics
-
Machine Learning for Healthcare Analytics Projects. Build smart AI applications using neural network methodologies across the healthcare vertical market
-
Machine Learning with scikit-learn Quick Start Guide. Classification, regression, and clustering techniques in Python
-
R Graphics Cookbook. Practical Recipes for Visualizing Data. 2nd Edition
-
Matplotlib 3.0 Cookbook. Over 150 recipes to create highly detailed interactive visualizations using Python
-
Redash v5 Quick Start Guide. Create and share interactive dashboards using Redash
-
IBM Watson Projects. Eight exciting projects that put artificial intelligence into practice for optimal business performance
-
Hands-On Neural Network Programming with C#. Add powerful neural network capabilities to your C# enterprise applications
-
Mastering Predictive Analytics with scikit-learn and TensorFlow. Implement machine learning techniques to build advanced predictive models using Python
-
Mastering Puppet 5. Optimize enterprise-grade environment performance with Puppet
-
Voicebot and Chatbot Design. Flexible conversational interfaces with Amazon Alexa, Google Home, and Facebook Messenger
-
MicroStrategy Quick Start Guide. Data analytics and visualizations for Business Intelligence
-
Applied Data Visualization with R and ggplot2. Create useful, elaborate, and visually appealing plots
-
Python Data Science Essentials. A practitioner’s guide covering essential data science principles, tools, and techniques - Third Edition
-
Getting Started with Tableau 2018.x. Get up and running with the new features of Tableau 2018 for impactful data visualization
Poznaj techniki przetwarzania i analizy danych z książkami o Big Data dostępnymi w księgarni Helion
Nasza kategoria książek o Big Data oferuje bogaty zbiór publikacji, które wprowadzają w świat przetwarzania i analizy ogromnych zbiorów danych. Wśród nich znajdują się pozycje takie jak "Big Data. Najlepsze praktyki budowy skalowalnych systemów obsługi danych w czasie rzeczywistym" oraz "Hadoop. Kompletny przewodnik. Analiza i przechowywanie danych", które są doskonałym wyborem dla osób chcących praktycznie podejść do tematu Big Data. Nasz asortyment obejmuje również zaawansowane publikacje, które umożliwiają pogłębienie wiedzy i rozwijanie umiejętności w zakresie zaawansowanej analizy danych.
Dodatkowo, oferujemy książki skoncentrowane na konkretnych narzędziach i technologiach związanych z Big Data. Wśród nich wyróżniają się tytuły poświęcone Apache Spark i zastosowaniom uczenia maszynowego w przetwarzaniu dużych zbiorów danych. Są to idealne pozycje dla tych, którzy chcą specjalizować się w konkretnych technikach i narzędziach Big Data.
Książki o Big Data - twoje źródło wiedzy o “wielkich danych”
W Helion dbamy o to, aby nasze książki były nie tylko bogatym źródłem wiedzy teoretycznej, ale także praktycznym przewodnikiem, który umożliwia zastosowanie tej wiedzy w realnych warunkach pracy. Dlatego też nasze publikacje zawierają liczne przykłady, studia przypadków oraz praktyczne wskazówki, które pomogą Ci z sukcesem zrealizować projekty związane z Big Data.
Zapraszamy do zapoznania się z naszą ofertą książek o Big Data. W Helion znajdziesz literaturę, która pozwoli Ci nie tylko zrozumieć, ale także efektywnie wykorzystać potencjał “wielkich danych” w Twojej pracy zawodowej. Niezależnie od tego, czy jesteś studentem, początkującym analitykiem czy doświadczonym specjalistą IT, nasze książki mogą stanowić cenne źródło wiedzy i inspiracji. Odkryj razem z nami fascynujący świat Big Data!