Ґері В. Левандовскi - ebooki
Tytuły autora: Ґері В. Левандовскi dostępne w księgarni Ebookpoint
-
R Machine Learning By Example. Understand the fundamentals of machine learning with R and build your own dynamic algorithms to tackle complicated real-world problems successfully
-
Mastering .NET Machine Learning. Use machine learning in your .NET applications
-
Learning Responsive Data Visualization. Create stunning data visualizations that look awesome on every device and screen resolutions
-
Learning QGIS. Create great maps and perform geoprocessing tasks with ease - Third Edition
-
Elasticsearch Server. Leverage Elasticsearch to create a robust, fast, and flexible search solution with ease - Third Edition
-
Regression Analysis with Python. Discover everything you need to know about the art of regression analysis with Python, and change how you view data
-
Real-Time Big Data Analytics. Design, process, and analyze large sets of complex data in real time
-
Google Analytics. Integracja i analiza danych
-
Learning Predictive Analytics with Python. Click here to enter text
-
Elasticsearch Essentials. Harness the power of ElasticSearch to build and manage scalable search and analytics solutions with this fast-paced guide
-
Splunk Developer's Guide. Learn the A to Z of building excellent Splunk applications with the latest techniques using this comprehensive guide - Second Edition
-
R Data Science Essentials. R Data Science Essentials
-
Learning Hunk. A quick, practical guide to rapidly visualizing and analyzing your Hadoop data using Hunk
-
Elasticsearch Indexing. How to Improve User’s Search Experience
-
Mathematica Data Analysis. Learn and explore the fundamentals of data analysis with power of Mathematica
-
Monitoring Docker. Monitor your Docker containers and their apps using various native and third-party tools with the help of this exclusive guide!
-
Apache Oozie Essentials. Unleash the power of Apache Oozie to create and manage your big data and machine learning pipelines in one go
-
Python Data Visualization Cookbook. Visualize data using Python's most popular libraries
-
Test-Driven Machine Learning. Control your machine learning algorithms using test-driven development to achieve quantifiable milestones
-
Spark. Zaawansowana analiza danych
-
Hadoop. Komplety przewodnik. Analiza i przechowywanie danych
-
Kibana Essentials. Use the functionalities of Kibana to discover data and build attractive visualizations and dashboards for real-world scenarios
-
Data Analysis with Stata. Explore the big data field and learn how to perform data analytics and predictive modelling in STATA
-
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 Machine Learning with R. Master machine learning techniques with R to deliver insights for complex projects
-
Data Analysis and Business Modeling with Excel 2013. Manage, analyze, and visualize data with Microsoft Excel 2013 to transform raw data into ready to use information
-
Mastering Python Data Visualization. Generate effective results in a variety of visually appealing charts using the plotting packages in Python
-
Creating Stunning Dashboards with QlikView. Bring real business insights to your company through effective and engaging dashboards in QlikView
-
Apache Mahout Clustering Designs. Explore clustering algorithms used with Apache Mahout
-
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
-
Mastering Social Media Mining with R. Extract valuable data from your social media sites and make better business decisions using R
-
Python Machine Learning. Learn how to build powerful Python machine learning algorithms to generate useful data insights with this data analysis tutorial
-
Sharing Big Data Safely. Managing Data Security
-
Apache Spark Graph Processing. Build, process and analyze large-scale graph data effectively with Spark
-
Mastering Python for Data Science. Explore the world of data science through Python and learn how to make sense of data
-
Learning YARN. Moving beyond MapReduce - learn resource management and big data processing using YARN
-
Metody i techniki odkrywania wiedzy. Narzędzia CAQDAS w procesie analizy danych jakościowych
-
OpenGL Data Visualization Cookbook. Over 35 hands-on recipes to create impressive, stunning visuals for a wide range of real-time, interactive applications using OpenGL
-
Spark Cookbook. With over 60 recipes on Spark, covering Spark Core, Spark SQL, Spark Streaming, MLlib, and GraphX libraries this is the perfect Spark book to always have by your side
-
Analiza danych w naukach ścisłych i technice
-
Hadoop Security. Protecting Your Big Data Platform
-
ggplot2 Essentials. Explore the full range of ggplot2 plotting capabilities to create meaningful and spectacular graphs
-
NumPy: Beginner's Guide. Build efficient, high-speed programs using the high-performance NumPy mathematical library
-
Apache Mahout Essentials. Implement top-notch machine learning algorithms for classification, clustering, and recommendations with Apache Mahout
-
Microsoft Azure Machine Learning. Explore predictive analytics using step-by-step tutorials and build models to make prediction in a jiffy with a few mouse clicks
-
Graph Databases. New Opportunities for Connected Data. 2nd Edition
-
Sencha Charts Essentials. Create stunning charts and visualizations for both web and mobile applications
-
Mastering pandas for Finance. Master pandas, an open source Python Data Analysis Library, for financial data analysis
-
Mastering Python for Finance. Understand, design, and implement state-of-the-art mathematical and statistical applications used in finance with Python
-
Monitoring Hadoop. Get to grips with the intricacies of Hadoop monitoring using the power of Ganglia and Nagios
-
Data Visualization with D3 and AngularJS. Build dynamic and interactive visualizations from real-world data with D3 on AngularJS
-
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
-
Learning Three.js - the JavaScript 3D Library for WebGL. Create stunning 3D graphics in your browser using the Three.js JavaScript library
-
Learning Apache Mahout. Acquire practical skills in Big Data Analytics and explore data science with Apache Mahout
-
Natural Language Processing with Java. Explore various approaches to organize and extract useful text from unstructured data using Java
-
Real-time Analytics with Storm and Cassandra. Solve real-time analytics problems effectively using Storm and Cassandra
-
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 SciPy for Numerical and Scientific Computing. Quick solutions to complex numerical problems in physics, applied mathematics, and science with SciPy
-
Learning Hadoop 2. Design and implement data processing, lifecycle management, and analytic workflows with the cutting-edge toolbox of Hadoop 2
-
Mastering Scientific Computing with R. Employ professional quantitative methods to answer scientific questions with a powerful open source data analysis environment
-
Three.js Cookbook. Over 80 shortcuts, solutions, and recipes that allow you to create the most stunning visualizations and 3D scenes using the Three.js library
-
R Data Visualization Cookbook. Over 80 recipes to analyze data and create stunning visualizations with R
-
Clojure Data Analysis Cookbook. Dive into data analysis with Clojure through over 100 practical recipes for every stage of the analysis and collection process
-
HDInsight Essentials. Learn how to build and deploy a modern big data architecture to empower your business
-
Learning D3.js Mapping. Build stunning maps and visualizations using D3.js
-
Moodle Grad
-
Scala for Machine Learning. Leverage Scala and Machine Learning to construct and study systems that can learn from data
-
Uczenie maszynowe dla programistów
-
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
-
Highcharts Essentials. Create interactive data visualization charts with the Highcharts JavaScript library
-
Python Data Analysis. Learn how to apply powerful data analysis techniques with popular open source Python modules
-
R Graphs Cookbook. Over 70 recipes for building and customizing publication-quality visualizations of powerful and stunning R graphs
-
Thoughtful Machine Learning. A Test-Driven Approach
-
IPython Interactive Computing and Visualization Cookbook. Harness IPython for powerful scientific computing and Python data visualization with this collection of more than 100 practical data science recipes
-
Mathematica Data Visualization. Create and prototype interactive data visualizations using Mathematica
-
R Graph Essentials
-
Using Flume. Flexible, Scalable, and Reliable Data Streaming
-
Python 3 Text Processing with NLTK 3 Cookbook
-
Mastering D3.js. Bring your data to life by creating and deploying complex data visualizations with D3.js
-
Practical Machine Learning: Innovations in Recommendation
-
Practical Machine Learning: A New Look at Anomaly Detection
-
Haskell Data Analysis Cookbook. Explore intuitive data analysis techniques and powerful machine learning methods using over 130 practical recipes
-
Learning NumPy Array. Supercharge your scientific Python computations by understanding how to use the NumPy library effectively
-
Mastering Clojure Data Analysis. If you’d like to apply your Clojure skills to performing data analysis, this is the book for you. The example based approach aids fast learning and covers basic to advanced topics. Get deeper into your data
-
Pig Design Patterns. Simplify Hadoop programming to create complex end-to-end Enterprise Big Data solutions with Pig
-
Analiza i prezentacja danych w Microsoft Excel. Vademecum Walkenbacha. Wydanie II
-
Metoda Lean Analytics. Zbuduj sukces startupu w oparciu o analizę danych
-
Minitab Cookbook. With over 110 practical recipes, this is the ideal book for all statisticians who want to explore the vast capabilities of Minitab to organize data, analyze it, and visualize it with impactful graphs
-
Optimizing Hadoop for MapReduce. This book is the perfect introduction to sophisticated concepts in MapReduce and will ensure you have the knowledge to optimize job performance. This is not an academic treatise; it’s an example-driven tutorial for the real world
-
Getting Started with Flurry Analytics. In today's mobile app market you need to track your applications and analyze user data to give yourself the competitive edge. Flurry Analytics will do all that and more, and this book is the perfect developer's guide
-
Programming Elastic MapReduce. Using AWS Services to Build an End-to-End Application
-
Microsoft System Center Configuration Manager. Deploy a scalable solution by ensuring high availability and disaster recovery using Configuration Manager with this book and
-
ZooKeeper. Distributed Process Coordination
-
Excel 2013 PL. Kurs
-
Business Intelligence with MicroStrategy Cookbook. Over 90 practical, hands-on recipes to help you build your MicroStrategy business intelligence project, including more than a 100 screencasts with this book and
-
Getting Started with Simulink. Written by an experienced engineer, this book will help you utilize the great user-friendly features of Simulink to advance your modeling, testing, and interfacing skills. Packed with illustrations and step-by-step walkthroughs
-
Pentaho Data Integration Beginner's Guide. Get up and running with the Pentaho Data Integration tool using this hands-on, easy-to-read guide with this book and ebook - Second Edition
-
Doing Data Science. Straight Talk from the Frontline
-
The Culture of Big Data
-
On Being a Data Skeptic
-
Oracle Database 12c Backup and Recovery Survival Guide. A comprehensive guide for every DBA to learn recovery and backup solutions
-
Feedback Control for Computer Systems. Introducing Control Theory to Enterprise Programmers
-
Learning R. A Step-by-Step Function Guide to Data Analysis
-
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
-
Tabele i wykresy przestawne od A do Z - dynamiczna analiza dużych zbiorów danych
-
Clean Data
-
NumPy Cookbook
-
Building Machine Learning Systems with Python
-
Machine Learning with R Cookbook
-
R Packages
-
Learning Big Data with Amazon Elastic MapReduce
-
Making Big Data Work for Your Business. A clear, practical and simple guide to ensuring effective Big Data analytics for your business
-
Big Data. Rewolucja, która zmieni nasze myślenie
-
Big Data Analytics with R and Hadoop. If you're an R developer looking to harness the power of big data analytics with Hadoop, then this book tells you everything you need to integrate the two. You'll end up capable of building a data analytics engine with huge potential