Ronald T. Kneusel - książki
Tytuły autora: dostępne w księgarni Ebookpoint
-
Microsoft Power BI Complete Reference. Bring your data to life with the powerful features of Microsoft Power BI
-
Blockchain By Example. A developer's guide to creating decentralized applications using Bitcoin, Ethereum, and Hyperledger
-
Practical Site Reliability Engineering. Automate the process of designing, developing, and delivering highly reliable apps and services with SRE
-
Hands-On Data Science with SQL Server 2017. Perform end-to-end data analysis to gain efficient data insight
-
Julia 1.0 Programming Cookbook. Over 100 numerical and distributed computing recipes for your daily data science work?ow
-
Mastering Matplotlib 2.x. Effective Data Visualization techniques with Python
-
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
-
Data science od podstaw. Analiza danych w Pythonie
-
Deep Learning. Uczenie głębokie z językiem Python. Sztuczna inteligencja i sieci neuronowe
-
Mastering Puppet 5. Optimize enterprise-grade environment performance with Puppet
-
Redash v5 Quick Start Guide. Create and share interactive dashboards using Redash
-
Voicebot and Chatbot Design. Flexible conversational interfaces with Amazon Alexa, Google Home, and Facebook Messenger
-
R Programming Fundamentals. Deal with data using various modeling techniques
-
Hands-On Dashboard Development with Shiny. A practical guide to building effective web applications and dashboards
-
Hands-On Artificial Intelligence for Search. Building intelligent applications and perform enterprise searches
-
Hands-On Convolutional Neural Networks with TensorFlow. Solve computer vision problems with modeling in TensorFlow and Python
-
Uczenie maszynowe z użyciem Scikit-Learn i TensorFlow
-
Building Machine Learning Systems with Python. Explore machine learning and deep learning techniques for building intelligent systems using scikit-learn and TensorFlow - Third Edition
-
Microsoft Power BI Quick Start Guide. Build dashboards and visualizations to make your data come to life
-
Ethereum Projects for Beginners. Build blockchain-based cryptocurrencies, smart contracts, and DApps
-
Hands-On Data Warehousing with Azure Data Factory. ETL techniques to load and transform data from various sources, both on-premises and on cloud
-
Implementing Oracle API Platform Cloud Service. Design, deploy, and manage your APIs in Oracle’s new API Platform
-
Mastering Microsoft Power BI. Expert techniques for effective data analytics and business intelligence
-
Splunk 7 Essentials. Demystify machine data by leveraging datasets, building reports, and sharing powerful insights - Third Edition
-
Teradata Cookbook. Over 85 recipes to implement efficient data warehousing solutions
-
Python Web Scraping Cookbook. Over 90 proven recipes to get you scraping with Python, microservices, Docker, and AWS
-
OpenCV 3.x with Python By Example. Make the most of OpenCV and Python to build applications for object recognition and augmented reality - Second Edition
-
Making Data Visual. A Practical Guide to Using Visualization for Insight
-
SciPy Recipes. A cookbook with over 110 proven recipes for performing mathematical and scientific computations
-
SQL Server 2017 Administrator's Guide. One stop solution for DBAs to monitor, manage, and maintain enterprise databases
-
MySQL 8 for Big Data. Effective data processing with MySQL 8, Hadoop, NoSQL APIs, and other Big Data tools
-
Microsoft Power BI Cookbook. Over 100 recipes for creating powerful Business Intelligence solutions to aid effective decision-making
-
Machine Learning With Go. Implement Regression, Classification, Clustering, Time-series Models, Neural Networks, and More using the Go Programming Language
-
Network Security Through Data Analysis. From Data to Action. 2nd Edition
-
Mastering Machine Learning with Spark 2.x. Harness the potential of machine learning, through spark
-
Mastering Predictive Analytics with R. Machine learning techniques for advanced models - Second Edition
-
Learning TensorFlow. A Guide to Building Deep Learning Systems
-
Hands-On Deep Learning with TensorFlow. Uncover what is underneath your data!
-
Mastering Machine Learning with scikit-learn. Apply effective learning algorithms to real-world problems using scikit-learn - Second Edition
-
Machine Learning for OpenCV. Intelligent image processing with Python
-
Mastering Java Machine Learning. A Java developer's guide to implementing machine learning and big data architectures
-
Learning pandas. High performance data manipulation and analysis using Python - Second Edition
-
QlikView for Developers. Design and build scalable and maintainable BI solutions
-
R: Mining spatial, text, web, and social media data. Create and customize data mining algorithms
-
Data Science i uczenie maszynowe
-
Python: End-to-end Data Analysis. Leverage the power of Python to clean, scrape, analyze, and visualize your data
-
D3.js 4.x Data Visualization. Learn to visualize your data with JavaScript - Third Edition
-
Mastering OpenCV 3. Get hands-on with practical Computer Vision using OpenCV 3 - Second Edition
-
Python Deep Learning. Next generation techniques to revolutionize computer vision, AI, speech and data analysis
-
QGIS:Becoming a GIS Power User. Master data management, visualization, and spatial analysis techniques in QGIS and become a GIS power user
-
Splunk: Enterprise Operational Intelligence Delivered. Machine data made accessible
-
Windows Server 2016 Hyper-V Cookbook. Save time and resources by getting to know the best practices and intelligence from industry experts - Second Edition
-
Efficient R Programming. A Practical Guide to Smarter Programming
-
Tableau 10 Business Intelligence Cookbook. Create powerful, effective visualizations with Tableau 10
-
Programming Pig. Dataflow Scripting with Hadoop. 2nd Edition
-
Analiza biznesowa. Praktyczne modelowanie organizacji
-
Advanced Machine Learning with Python. Solve challenging data science problems by mastering cutting-edge machine learning techniques in Python
-
Mastering Python Data Analysis. Become an expert at using Python for advanced statistical analysis of data using real-world examples
-
R: Data Analysis and Visualization. Click here to enter text
-
Learning Probabilistic Graphical Models in R. Familiarize yourself with probabilistic graphical models through real-world problems and illustrative code examples in R
-
Google Analytics. Integracja i analiza danych
-
Elasticsearch Essentials. Harness the power of ElasticSearch to build and manage scalable search and analytics solutions with this fast-paced guide
-
Test-Driven Machine Learning. Control your machine learning algorithms using test-driven development to achieve quantifiable milestones
-
Learning Bayesian Models with R. Become an expert in Bayesian Machine Learning methods using R and apply them to solve real-world big data problems
-
Mastering Data Analysis with R. Gain sharp insights into your data and solve real-world data science problems with R—from data munging to modeling and visualization
-
Building a Recommendation System with R. Learn the art of building robust and powerful recommendation engines using R
-
Big Data for Chimps. A Guide to Massive-Scale Data Processing in Practice
-
Sharing Big Data Safely. Managing Data Security
-
Mastering pandas for Finance. Master pandas, an open source Python Data Analysis Library, for financial data analysis
-
Scaling Big Data with Hadoop and Solr. Understand, design, build, and optimize your big data search engine with Hadoop and Apache Solr
-
Learning pandas. Get to grips with pandas - a versatile and high-performance Python library for data manipulation, analysis, and discovery
-
Interactive Applications Using Matplotlib
-
Real-World Hadoop
-
Mastering R for Quantitative Finance. Use R to optimize your trading strategy and build up your own risk management system
-
Learning Hadoop 2. Design and implement data processing, lifecycle management, and analytic workflows with the cutting-edge toolbox of Hadoop 2
-
Zwinna analiza danych. Apache Hadoop dla każdego
-
R Machine Learning Essentials. Gain quick access to the machine learning concepts and practical applications using the R development environment
-
Badanie danych. Raport z pierwszej linii działań
-
Practical Machine Learning: Innovations in Recommendation
-
Practical Machine Learning: A New Look at Anomaly Detection
-
Analiza i prezentacja danych w Microsoft Excel. Vademecum Walkenbacha. Wydanie II
-
Anonymizing Health Data. Case Studies and Methods to Get You Started
-
Doing Data Science. Straight Talk from the Frontline
-
Puppet 3 Cookbook. An essential book if you have responsibility for servers. Real-world examples and code will give you Puppet expertise, allowing more control over servers, cloud computing, and desktops. A time-saving, career-enhancing tutorial - Second Edition
-
Building Machine Learning Systems with Python. Expand your Python knowledge and learn all about machine-learning libraries in this user-friendly manual. ML is the next big breakthrough in technology and this book will give you the head-start you need
-
Analiza i prezentacja danych w Microsoft Excel. Vademecum Walkenbacha
-
Instant MapReduce Patterns - Hadoop Essentials How-to. Practical recipes to write your own MapReduce solution patterns for Hadoop programs
-
QlikView 11 for Developers. This book is smartly built around a practical case study – HighCloud Airlines – to help you gain an in-depth understanding of how to build applications for Business Intelligence using QlikView. A superb hands-on guide
-
Getting Started with Storm
-
How Data Science Is Transforming Health Care
-
Hurtownie danych. Od przetwarzania analitycznego do raportowania
-
Microsoft SQL Server. Modelowanie i eksploracja danych
-
Designing Data Visualizations. Representing Informational Relationships
-
21 Recipes for Mining Twitter. Distilling Rich Information from Messy Data
-
Beautiful Visualization. Looking at Data through the Eyes of Experts
-
Head First Data Analysis. A learner's guide to big numbers, statistics, and good decisions
-
XSLT. 2nd Edition
-
Harnessing Hibernate
-
Web Mapping Illustrated. Using Open Source GIS Toolkits
-
Excel 2013. Kurs video. Poziom drugi. Przetwarzanie i analiza danych
-
Big Data Processing with Apache Spark. Efficiently tackle large datasets and big data analysis with Spark and Python
-
Tableau 10 Bootcamp. Intensive training for data visualization and dashboarding
-
Poznajemy Sparka. Błyskawiczna analiza danych
-
Building Machine Learning Systems with Python
-
Data science, trudne elementy. Jak stać się ekspertem w danologii
-
Matematyka w deep learningu. Co musisz wiedzieć, aby zrozumieć sieci neuronowe