Data mining
Resource Information
The concept Data mining represents the subject, aboutness, idea or notion of resources found in Sydney Jones Library, University of Liverpool.
The Resource
Data mining
Resource Information
The concept Data mining represents the subject, aboutness, idea or notion of resources found in Sydney Jones Library, University of Liverpool.
- Label
- Data mining
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- http://id.loc.gov/authorities/subjects/sh97002073
643 Items that share the Concept Data mining
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- 2016 IEEE International Congress on Big Data (BigData Congress)
- 97 THINGS EVERY DATA ENGINEER SHOULD KNOW
- A guide to improving data integrity and adoption : a case study in verifying usage data
- A whirlwind tour of Python
- AI and analytics in production : how to make it work
- Accelerating discovery : mining unstructured information for hypothesis generation
- Actionable web analytics : using data to make smart business decisions
- Adaptive resonance theory in social media data clustering : roles, methodologies, and applications
- Advanced Jupyter Notebook development : deployment and customization of notebooks, tmpnb, nbviewer and JupyterHub
- Advanced analytics and real-time data processing in Apache Spark
- Advanced statistics and data mining for data science
- Advances in Computational Intelligence : 19th Mexican International Conference on Artificial Intelligence, MICAI 2020, Mexico City, Mexico, October 12-17, 2020, Proceedings, Part II
- Advancing into analytics: : from Excel to Python and R
- Agile data science
- Agile data science 2.0 : building full-stack data analytics applications with Spark
- Analiza danych w bizenesie : Sztuka podejmowania skutecznych decyzji
- Analyzing big data with Hadoop, AWS, and EMR : understanding how to use Hadoop on Amazon's Elastic MapReduce Service
- Analyzing big data with Spark and Amazon EMR : learning to harness the power of cloud computing to analyze big data when you don't have a cluster of your own
- Analyzing data in the Internet of Things : a collection of talks from Strata + Hadoop World 2015
- Analyzing data using Spark 2.0 DataFrames with Python : learning the basics of Python and Spark DataFrames, and how they work with big data
- Ancient manuscripts in digital culture : visualisation, data mining, communication
- Apache Spark 2 data processing and real-time analytics : master complex big data processing, stream analytics, and machine learning with Apache
- Apache Spark 2.0
- Apache Spark for data science cookbook : overinsightful 90 recipes to get lightning-fast analytics with Apache Spark
- Apache Spark with Python : big data with PySpark and Spark
- Apache Spark with Scala
- Apache Spark with Scala : learn Spark from a big data guru
- Applications of machine learning in wireless communications
- Applied Data Mining
- Applied Data Science Workshop - Second Edition
- Applied data analytics : principles and applications
- Applied data mining for business analytics
- Applied data mining for forecasting using SAS
- Applied modeling techniques and data analysis : finanicial, demographic, stochastic and statistical models and methods, 2
- Applied unsupervised learning with R
- Architectural considerations for Hadoop applications : using clickstream analytics as an end-to-end example
- Artificial Intelligence in Education : 20th International Conference, AIED 2019, Chicago, IL, USA, June 25-29, 2019, Proceedings, Part I
- Artificial Intelligence in Education : 20th International Conference, AIED 2019, Chicago, IL, USA, June 25-29, 2019, Proceedings, Part II
- Artificial Intelligence in Medicine : 16th Conference on Artificial Intelligence in Medicine, AIME 2017, Vienna, Austria, June 21-24, 2017, Proceedings
- Artificial intelligence in data mining : theories and applications
- Ask, measure, learn : using social media analytics to understand and influence customer behavior
- Authoring machine learning models from scratch
- Automatic detection of irony : opinion mining in microblogs and social media
- Automating Analytics
- Avro data
- Azure masterclass : analyze data with Azure Stream Analytics
- Azure masterclass : manage Azure cloud with ARM templates
- BUILDING AN EFFECTIVE DATA SCIENCE PRACTICE : a framework to bootstrap and manage a successful... data science practice
- BUSINESS INFORMATION SYSTEMS WORKSHOPS : bis 2020 international workshops
- Badanie danych Raport z pierwszej linii działań
- Basic statistics and data mining for data science
- Basic statistics and regression for machine learning in Python
- Become a Python data analyst
- Become a Python data analyst : perform exploratory data analysis and gain insight into scientific computing using Python
- Becoming a Data Head : How to Think, Speak, and Understand Data Science, Statistics, and Machine Learning
- Beginning data analysis with Python and Jupyter : use powerful industry-standard tools to unlock new, actionable insight from your existing data
- Beginning data analytics with RapidMiner : understanding core analytical methods and how to use them in RapidMiner
- Better intelligence from the new Google trends
- Beyond Spreadsheets with R
- Big Data : Entwicklung und Programmierung von Systemen für große Datenmengen und Einsatz der Lambda-Architektur
- Big Data For Dummies
- Big Data in Context: Legal, Social and Technological Insights
- Big Data, Mining, and Analytics : Components of Strategic Decision Making
- Big data : algorithms, analytics, and applications
- Big data : an art of decision making
- Big data : concepts, technology and architecture
- Big data : principles and best practices of scalable real-time data systems
- Big data : video edition
- Big data analytics beyond Hadoop : real-time applications with Storm, Spark, and more Hadoop alternatives
- Big data analytics for intelligent healthcare management
- Big data analytics for intelligent healthcare management
- Big data analytics using Apache Spark
- Big data analytics with Java : big data analytics - massive, predictive, social and self-driving
- Big data analytics with Spark : a practitioner's guide to using Spark for large-scale data processing, machine learning, and graph analytics, and high-velocity data stream processing
- Big data computing
- Big data demystified : how to use big data, data science and AI to make better business decisions and gain competitive advantage
- Big data for chimps : a guide to massive-scale data processing in practice
- Big data fundamentals : concepts, drivers & techniques
- Big data mining for climate change
- Big data now : 2014 edition : current perspectives from O'Reilly Media
- Big data now : 2015 edition : current perspectives from O'Reilly Media
- Big data now : 2016 edition : current perspectives from O'Reilly Media
- Big data now : current perspectives from O'Reilly radar
- Big data, open data and data development
- Broad learning through fusions : an application on social networks
- Building a big data analytics stack
- Building an intelligent Web : theory and practice
- Building better distributed data pipelines
- Building big data pipelines with Apache Beam : use a single programming model for both batch and stream data processing
- Building cognitive applications with IBM Watson services, Volume 1, Getting started
- Building data pipelines with Python : understanding pipeline frameworks, workflow automation, and Python toolsets
- Building data science applications with FastAPI : develop, manage, and deploy efficient machine learning applications with Python
- Building pipelines for natural language understanding with Spark : a hands-on guide to machine learning annotators, topic modeling, and deep learning for text mining
- Building the data-driven organization
- Business Information Systems workshops : BIS 2020 international workshops, Colorado Springs, CO, USA, June 8-10, 2020, revised selected papers
- Business Intelligence und Reporting mit Microsoft SQL Server 2008 : OLAP, data mining, analysis services, reporting services und integration services mit SQL Server 2008
- Business Process Management Forum : BPM Forum 2020, Seville, Spain, September 13-18, 2020, Proceedings
- Chinese Computational Linguistics : 19th China National Conference, CCL 2020, Hainan, China, October 30 - November 1, 2020, proceedings
- Cloudera Impala
- Collective intelligence in action
- Coming to grips with dangerous algorithms : algorithms power transformative technology but also present many threats to users - which raises the question of how to prevent and regulate against potential disaster
- Commercial data mining : processing, analysis and modeling for predictive analytics projects
- Communicating data with Tableau
- Complex pattern mining : new challenges, methods and applications
- Computational Intelligence Methods for Bioinformatics and Biostatistics : 13th International Meeting, CIBB 2016, Stirling, UK, September 1-3, 2016, Revised Selected Papers
- Computational Intelligent Data Analysis for Sustainable Development
- Computational intelligent data analysis for sustainable development
- Contemporary Experimental Design, Multivariate Analysis and Data Mining : Festschrift in Honour of Professor Kai-Tai Fang
- Contrast data mining : concepts, algorithms, and applications
- Contrast data mining : concepts, algorithms, and applications
- Core data analysis : summarization, correlation, and visualization
- Cracking the data science interview : what to expect and how to succeed
- Creating a culture of data-driven business
- Crowdsourcing for speech processing : applications to data collection, transcription and assessment
- Crowdsourcing for speech processing : applications to data collection, transcription and assessment
- Customer analytics for dummies
- Customer analytics for dummies
- Customer and business analytics : applied data mining for business decision making using R
- Customer segmentation and clustering using SAS Enterprise miner
- DATA ENGINEERING WITH APACHE SPARK : creating and deploying mission critical streaming applications
- DB2 10.5 with BLU Acceleration : new dynamic in-memory analytics for the era of big data
- DIGITAL ECONOMY. EMERGING TECHNOLOGIES AND BUSINESS INNOVATION : 5thInternational conference on digital economy, ICDEc 2020, Bucharest, Romania, June 11-13, 2020, proceedings
- Data Analysis and Applications 1
- Data Engineering with Apache Spark, Delta Lake, and Lakehouse
- Data Jujitsu
- Data Mining Using Grammar Based Genetic Programming and Applications
- Data Mining and Machine Learning in Cybersecurity
- Data Mining in Finance : Advances in Relational and Hybrid Methods
- Data Mining in Structural Dynamic Analysis : A Signal Processing Perspective
- Data Mining mit Microsoft SQL Server : Analyse und Mustererkennung in Daten mit Excel 2007 und SQL Server 2005/2008
- Data Mining on Multimedia Data
- Data Mining, 2nd Edition
- Data Science : Grundlagen, Architekturen und Anwendungen
- Data Science Programming All-In-One for Dummies
- Data Science mit Python : das Handbuch für den Einsatz von IPython, Jupyter, NumPy, Pandas, Matplotlib, Scikit-Learn
- Data Science, 2nd Edition
- Data Smart : using data science to transform information into insight
- Data Wrangling Workshop - Second Edition
- Data analysis and applications 3 : computational, classification, financial, statistical and stochastic methods
- Data analysis crash course for beginners : Pandas + Python
- Data analysis on streams
- Data analysis using SQL and Excel
- Data analysis with Python and Pyspark
- Data analytics for corporate debt markets : using data for investing, trading, capital markets, and portfolio management
- Data analytics for drilling engineering : theory, algorithms, experiments, software
- Data analytics made easy : use machine learning and data storytelling in your work without writing... any code
- Data analytics using Spark and Hadoop : learn how to integrate Spark and Hadoop in a series of hands-on labs
- Data and text processing for health and life sciences
- Data bootcamp
- Data cleansing master class in Python
- Data driven : creating a data culture
- Data engineering with Apache Spark, Delta Lake, and Lakehouse : create scalable data pipelines and networks that ingest, process, and store complex data
- Data infrastructure for next-gen finance
- Data infrastructure for next-gen finance : tools for cloud migration, customer even hubs, governance & security
- Data just right : introduction to large-scale data & analytics
- Data just right LiveLessons
- Data literacy : how to make your experiments robust and reproducible
- Data management and analysis : case studies in education, healthcare and beyond
- Data marketplaces
- Data mining : concepts and techniques
- Data mining : know it all
- Data mining : practical machine learning tools and techniques
- Data mining : theories, algorithms, and examples
- Data mining and machine learning applications
- Data mining and machine learning in cybersecurity
- Data mining for bioinformatics
- Data mining for bioinformatics applications
- Data mining for business intelligence : concepts, techniques, and applications in Microsoft Office Excel with XLMiner
- Data mining in biomedical imaging, signaling, and systems
- Data mining methods for the content analyst : an introduction to the computational analysis of content
- Data mining mobile devices
- Data mining techniques in CRM : inside customer segmentation
- Data mining techniques in grid computing environments
- Data mining tools for malware detection
- Data mining with Microsoft SQL server 2008
- Data munging with Hadoop
- Data pipelines with Apache Airflow
- Data pipelines with Apache Airflow
- Data preparation for analytics using SAS
- Data science : from research to application
- Data science : new issues, challenges and applications
- Data science and machine learning with Python--Hands on!
- Data science bookcamp : five Python projects
- Data science for business
- Data science for dummies
- Data science for dummies
- Data science for dummies
- Data science from scratch : first principles with Python
- Data science projects with Python : a case study approach to gaining valuable insights from real data with machine learning
- Data science projects with Python : a case study approach to successful data science projects using Python, pandas, and scikcit-learn
- Data science with Python : combine Python with machine learning principles to discover hidden patterns in raw data
- Data science with Python : unleash the power of Python and its robust data science capabilities : a course in four modules
- Data science with Python and Dask
- Data science with Python and R
- Data visualization recipes in Python
- Data wrangling and analysis with Python
- Data wrangling with Python : creating actionable data from raw sources
- Data wrangling with Python : tips and tools to make your life easier
- Data, engineering and applications, Volume 2
- Data-Science-Crashkurs : Eine interaktive und praktische Einführung
- Data-driven business decisions
- Database Systems for Advanced Applications : 25th International Conference, DASFAA 2020, Jeju, South Korea, September 24-27, 2020, Proceedings, Part II
- Database and expert systems applications : 31st International Conference, DEXA 2020, Bratislava, Czech Republic, September 14-17, 2020, Proceedings, Part II
- Database systems for advanced applications : 25th International Conference, DASFAA 2020, Jeju, South Korea, September 24-27, 2020, Proceedings, Part I
- Databases Theory and Applications : 28th Australasian Database Conference, ADC 2017, Brisbane, QLD, Australia, September 25-28, 2017, Proceedings
- Datenanalyse mit Python
- Datenanalyse mit Python : Auswertung von Daten mit Pandas, NumPy und IPython
- Datenanalyse von Kopf bis Fuß
- Deep learning : concepts, methodologies, tools, and applications
- Deep learning for health tech : neural network applications in healthcare using Python and TensorFlow
- Descriptive Data Mining
- Descriptive data mining
- Designing Cloud Data Platforms
- Designing and developing analytics-based data products : an increasing number of companies are creating products that combine data with analytical capabilities : creating an effective development process for these data products requires following well-established steps - and adding a few new ones, too
- Designing cloud data platforms
- Designing digital products for kids : deliver user experiences that delight kids, parents, and teachers
- Determine the right analytic database : a survey of data technologies and products
- Discovery Science : 23rd International Conference, DS 2020, Thessaloniki, Greece, October 19-21, 2020, Proceedings
- Does correlation prove causation in predictive analytics?
- Doing data science
- Dynamic and Seamless Integration of Production, Logistics and Traffic : Fundamentals of Interdisciplinary Decision Support
- Elasticsearch 7 quick start guide : get up and running with the distributed search and analytics capabilities of Elasticsearch
- Embedding analytics in modern applications : how to provide distraction-free insights to end users
- Emergency Response Decision Support System
- Encyclopedia of Machine Learning and Data Science
- Encyclopedia of big data
- Essential PySpark for Scalable Data Analytics
- Essential PySpark for data analytics : a beginner's guide to harnessing the power and ease of PySpark 3.0
- Ethics of big data
- Evaluating machine learning models : a beginner's guide to key concepts and pitfalls
- Event Mining
- Event Streams in Action
- Event mining : algorithms and applications
- Event mining for explanatory modeling
- Expert data wrangling with R : streamline your work with tidyr, dplyr, and ggvis
- Fashioning data : a 2015 update : data innovations from the fashion industry
- Fast data : smart and at scale : design patterns and recipes
- Fast data architectures for streaming applications : getting answers now from data sets that never end
- Feature engineering for machine learning : principles and techniques for data scientists
- Finding profit in your organization's data : three examples from the frontlines of IoT
- Focusing Solutions for Data Mining : Analytical Studies and Experimental Results in Real-World Domains
- Forecasting sales at Ska Brewing Company
- Foundations of data intensive applications : large scale data analytics under the hood
- From flat files to deconstructed databases : the evolution and future of the big data ecosystem
- Fundamentals of data analytics in Python LiveLessons
- Fundamentals of data engineering
- Fundamentals of predictive analytics with JMP
- Fundamentals of predictive analytics with JMP
- Fuzzy modeling and genetic algorithms for data mining and exploration
- Game Theory for Data Science: Eliciting Truthful Information
- Generating dynamic social networks from large scale unstructured data
- Getting analytics right : answering business questions with more data in less time
- Getting data right : tackling the challenges of big data volume and variety
- Getting started w/data pipelines
- Getting started with Beautiful Soup : build your own web scraper and learn all about web scraping with Beautiful Soup
- Getting started with Greenplum for big data analytics : a hands-on guide on how to execute an analytics project from conceptualization to operationalization using Greenplum
- Getting started with Python web scraping
- Getting started with SAS Enterprise Miner for machine learning : learning to perform segmentation and predictive modeling
- Getting started with SAS Enterprise miner 14.1
- Getting started with data science : making sense of data with analytics
- Global Knowledge Dynamics and Social Technology
- Go web scraping quick start guide : implement the power of Go to scrape and crawl data from the web
- Going pro in data science : what it takes to succeed as a professional data scientist
- Google BigQuery : the definitive guide : data warehousing, analytics, and machine learning at scale
- Graphing data with R : an introduction
- Guide to Contract Pricing, 5th Edition
- Hadoop fundamentals
- Hadoop fundamentals 2/e
- Handbook of research on emerging trends and applications of machine learning
- Hands-On Data Science with R : Techniques to Perform Data Manipulation and Mining to Build Smart Analytical Models Using R
- Hands-on big data modeling : effective database design techniques for data architects and business intelligence professionals
- Hands-on business intelligence with Qlik Sense : implement self-service data analytics with insights and guidance from Qlik Sense experts
- Hands-on data science and Python machine learning : perform data mining and machine learning efficiently using Python and Spark
- Hands-on data science with R : techniques to perform data manipulation and mining to build smart analytical models using R
- Hands-on machine learning for data mining
- Hands-on machine learning with Microsoft Excel 2019 : build complete data analysis flows, from data collection to visualization
- Hands-on predictive analytics with Python : master the complete predictive analytics process, from problem definition to model deployment
- Hands-on recommendation systems with Python : start building powerful and personalized, recommendation engines with Python
- Hands-on with Amazon Redshift : large scale data warehouse design in the cloud
- Hardcore data science
- Head first data analysis
- Health Information Science : 9th International Conference, HIS 2020, Amsterdam, The Netherlands, October 20-23, 2020, Proceedings
- HealthCare's Corporate Social Responsibility Program
- How can I clean my data for use in a predictive model?
- How do I choose the correct predictive model for my organizational questions?
- How to use your data science team : becoming a data-driven organization
- IBM SPSS Modeler essentials
- IBM SPSS modeler essentials : effective techniques for building powerful data mining and predictive analytics solutions
- IBM Watson Content Analytics : discovering actionable insight from your content
- IBM Watson projects : eight exciting projects that put artificial intelligence into practice for optimal business performance
- IBM content analytics version 2.2 : discovering actionable insight from your content
- IBM software defined infrastructure for big data analytics workloads
- IBM storage solutions for Splunk enterprise
- Illustrating Statistical Procedures: Finding Meaning in Quantitative Data
- Implementing Qlik Sense : design, develop, and validate BI solutions for consultants
- Implementing Splunk 7 : effective operational intelligence to transform machine-generated data into valuable business insight
- Implementing Splunk : a comprehensive guide to help you transform big data into valuable business insights with Splunk 6.2
- Individual and Collective Graph Mining: Principles, Algorithms, and Applications
- Information Quality in Information Fusion and Decision Making
- Information security risk assessment toolkit : practical assessments through data collection and data analysis
- Innovating With Analytics
- Innovations in big data mining and embedded knowledge
- Integrated analytics : platforms and principles for centralizing your data
- Integrating Analytics in Your Organization : Lessons from the Sports Industry
- Integrierte Business-Informationssysteme : ERP, SCM, CRM, BI, Big Data Analytics - Prozesssimulation, Rollenspiel, Serious Gaming
- Intelligent Computing Methodologies : 16th International Conference, ICIC 2020, Bari, Italy, October 2-5, 2020, Proceedings, Part III
- Intelligent Tutoring Systems : 15th International Conference, ITS 2019, Kingston, Jamaica, June 3-7, 2019, Proceedings
- Intelligent data analysis : from data gathering to data comprehension
- Intelligent data analytics for terror threat prediction : architectures, methodologies, techniques and applications
- Intelligent data mining and fusion systems in agriculture
- Intelligent systems : 9th Brazilian Conference, BRACIS 2020, Rio Grande, Brazil, October 20-23, 2020, Proceedings, Part I
- Internet of Things and Data Analytics Handbook
- Internet of things and data analytics handbook
- Internet-scale pattern recognition : new techniques for voluminous data sets and data clouds
- Introducing data science : big data, machine learning, and more, using Python tools
- Introduction : mining the tar sands of big data
- Introduction to Apache Spark 2.0 : a primer on Spark 2.0 fundamentals and architecture
- Introduction to Pandas for developers : understand the basic workflows and gotchas of crawling, munging and plotting data
- Introduction to algorithms for data mining and machine learning
- Introduction to data analytics with KNIME : a data science approach to analytics
- Introduction to machine learning with Python : a guide for data scientists
- Introduction to statistical and machine learning methods for data science
- Introduction to the Amazon Elasticsearch Service : learn to search and analyze big data using the Amazon Elasticsearch Service (ES)
- Introduction to the Microsoft Cortana Intelligence Suite for advanced analytics : how to utilize CIS and the Azure team data science process for intelligent applications
- JMP Essentials, 2nd Edition
- JMP version 11 : Using JMP
- Jing tong ji qi xue xi : shi yong Python = Introduction to machine learning with Python
- Jupyter Notebook for data science
- Jupyter cookbook : over 75 recipes to perform interactive computing across Python, R, Scala, Spark, JavaScript, and more
- Kibana 7 quick start guide : visualize your Elasticsearch data with ease
- Kibana essentials : use the functionalities of Kibana to reveal insights from the data and build attractive visualizations and dashboards for real-world scenarios
- Knowledge Management in Digital Change : New Findings and Practical Cases
- Knowledge discovery from data streams
- Knowledge discovery process and methods to enhance organizational performance
- Knowledge science : modeling the knowledge creation process
- Large-Scale Parallel Data Mining
- Large-scale real-time stream processing and analytics : how to gain insight from fast data
- Learn Hadoop and Azure HDInsight basics this evening (in 2 hours)
- Learn Qlik Sense dashboard development
- Learn RStudio IDE : Quick, Effective, and Productive Data Science
- Learn data mining through Excel : a step-by-step approach for understanding machine learning methods
- Learning Analytics Cookbook : How to Support Learning Processes Through Data Analytics and Visualization
- Learning Apache Apex : Real-time streaming applications with Apex
- Learning ELK stack : build mesmerizing visualizations, and analytics from your logs and data using Elasticsearch, Logstash, and Kibana
- Learning Elasticsearch : distributed real-time search and analytics with Elasticsearch 5.x
- Learning Google BigQuery : a beginner's guide to mining massive datasets through interactive analysis
- Learning GraphQL : declarative data fetching for modern web apps
- Learning IPython for interactive computing and data visualization : get started with Python for data analysis and numerical computing in the Jupyter notebook
- Learning Jupyter 5 : explore interactive computing using Python, Java, JavaScript, R, Julia, and JupyterLab
- Learning Jupyter : learn how to write code, mathematics, graphics, and output, all in a single document as well as in a web browser using Project Jupyter
- Learning Kibana 5.0 : exploit the visualization capabilities of Kibana and build powerful interactive dashboards
- Learning Pentaho data integration 8 CE : an end-to-end guide to exploring, transforming, and integrating your data across multiple sources
- Learning Python data analysis
- Learning Python for data science
- Learning Qlik Sense : the official guide : get the most out of your Qlik Sense investment with the latest insight and guidance direct from the Qlik Sense team
- Learning Scrapy : learn the art of efficient web scraping and crawling with Python
- Learning Spark SQL : architect streaming analytics and machine learning solutions
- Learning Splunk Web Framework : take your analytics online with the ease and power of the Splunk Web Framework
- Learning data mining with Python : use Python to manipulate data and build predictive models
- Learning social media analytics with R : transform data from social media platforms into actionable insights
- Learning web scraping with JavaScript
- Lessons From Becoming a Data-Driven Organization
- Leveraging multi-CDN at Riot Games
- Linear methods for optimization and prediction in healthcare : make causal inferences in health data using R and Python
- MAD skills
- Machine Learning for Authorship Attribution and Cyber Forensics
- Machine Learning mit Python : das Praxis-Handbuch für Data Science, Predictive Analytics und Deep Learning
- Machine Learning mit Python und Scikit-learn und TensorFlow : das umfassende Praxis-Handbuch für Data Science, Deep Learning und Predictive Analytics
- Machine Learning with Pytorch and Scikit-Learn : Develop Machine Learning and Deep Learning Models with Python
- Machine learning and data mining in aerospace technology
- Machine learning and data science with Python : a complete beginners guide
- Machine learning avec Python
- Machine learning in the cloud with Azure machine learning
- Making predictions with data and Python
- Making sense of data : a practical guide to exploratory data analysis and data mining
- Making sense of stream processing : the philosophy behind Apache Kafka and scalable stream data platforms
- Mapping big data : a data-driven market report
- Marketing data science : modeling techniques in predictive analytics with R and Python
- Master competitive analytics with Oracle Endeca information discovery
- Mastering Apache Spark 2.x : scalable analytics faster than ever
- Mastering Java for data science : building data science applications in Java
- Mastering Kibana 6.x : visualize your Elastic Stack data with histograms, maps, charts, and graphs
- Mastering Python for data science : explore the world of data science through Python and learn how to make sense of data
- Mastering Qlik Sense
- Mastering Qlik Sense : expert techniques on self-service data analytics to create enterprise ready business intelligence solutions
- Mastering Spark for data science : master the techniques and sophisticated analytics used to construct Spark-based solutions that scale to deliver production-grade data science products
- Mastering Spark for structured streaming : building end-to-end structured streaming applications with Spark 2.0
- Mastering computer vision problems with state-of-the-art deep learning architectures, MXNet, and GPU virtual machines
- Mastering data analysis with R : gain clear insights into your data and solve real-world data science problems with R--from data munging to modeling and visualization
- Mastering data mining with Python : find patterns hidden in your data : learn how to create more powerful data mining applications with this comprehensive Python guide to advance data analytics techniques
- Mastering predictive analytics with scikit-learn and TensorFlow : implement machine learning techniques to build advanced predictive models using Python
- Mastering social media analytics : use data to build a business strategy
- Mastering social media mining with Python : acquire and analyze data from all corners of the social web with Python
- Mastering text mining with R : master text-taming techniques and build effective text-processing applications with R
- Mastering the SAS DS2 procedure : advanced data wrangling techniques
- Mastering the SAS DS2 procedure : advanced data-wrangling techniques
- Mathematical Modeling of Social Relationships : What Mathematics Can Tell Us About People
- Matthew Russell on mining the social web
- Medical Image Understanding and Analysis : 21st Annual Conference, MIUA 2017, Edinburgh, UK, July 11-13, 2017, Proceedings
- Meet the Expert : Kate Strachnyi on Building a Data Brand
- Merkmalskonstruktion für Machine Learning : Prinzipien und Techniken der Datenaufbereitung
- Methodologies for Knowledge Discovery and Data Mining : Third Pacific-Asia Conference, PAKDD-99 Beijing, China, April 26-28, 1999 Proceedings
- Methods in algorithmic analysis
- 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
- Microsoft Excel Pivot-Tabellen : das Praxisbuch : Ideen und Lösungen für die Datenanalyse mit PivotTables und PivotCharts mit intensivem Einstieg in Power Pivot für Version 2010, 2013 und 2016
- Mining social media : finding stories in Internet data
- Mining software engineering data for software reuse
- Mining the Web : discovering knowledge from hypertext data
- Mining the social web
- Mining the social web
- Mining the social web : Twitter
- Mining the social web, Facebook : learn how to explore and analyze Facebook data with Python and Facebook's Graph API
- Mining the social web, GitHub : using Python and NetworkX to gain insight into GitHub's usage and community of users
- Mining the social web, LinkedIn : learn how to access, download, analyze, and visualize LinkedIn data
- Mining the social web, mailboxes : learn to analyze and query large volumes of email using Python and Pandas
- Mining the talk : unlocking the business value in unstructured information
- Mining user generated content
- Mining your own business in banking : using DB2 Intelligent Miner for data
- Mining your own business in health care : using DB2 Intelligent Miner for data
- Mining your own business in retail : using DB2 Intelligent Miner for data
- Mining your own business in telecoms : using DB2 Intelligent Miner for data
- Mixture models and applications
- Modeling techniques in predictive analytics : business problems and solutions with R
- Modern analytics methodologies : driving business value with analytics
- Modern data mining algorithms in C++ and CUDA C : recent developments in feature extraction and selection algorithms for data science
- Mondrian in action : open source business analytics
- Monitoring with Ganglia
- Narragansett Brewing Company : Build a Brewery
- Nature-inspired computation in data mining and machine learning
- Network science with Python and NetworkX quick start guide : explore and visualize network data effectively
- New developments in large data techniques
- Next-generation big data : a practical guide to Apache Kudu, Impala, and Spark
- Not all data is created equal : balancing risk and reward in a data-driven economy
- Nullology
- Numbersense : how to use big data to your advantage
- Numerical computing with Python : harness the power of Python to analyze and find hidden patterns in the data
- O'Reilly Strata Conference : making data work
- O'Reilly Where conference 2012 : the business of location : complete video compilation
- OBIEE 11g reports and dashboards
- Opinion mining in information retrieval
- Oracle data integration : tools for harnessing data
- PRACTICAL FAIRNESS : achieving fair and secure data models
- PYTHON AND R FOR THE MODERN DATA SCIENTIST : the best of both worlds
- Pandas 1.x cookbook : practical recipes for scientific computing, time series analysis and exploratory data analysis using Python
- Pandas Brain Teasers
- Pandas data cleaning and modeling with Python
- Pandas shu ju fen xi
- Pandas shu ju qing xi yu jian mo
- Pentaho data integration : beginner's guide : get up and running with the Pentaho Data Integration tool using this hands-on, easy-to-read guide
- Pentaho data integration quick start guide : create ETL processes using Pentaho
- Pentaho solutions : business intelligence and data warehousing with Pentaho and MySQL
- Perspectives in Business Informatics Research : 19th International Conference on Business Informatics Research, BIR 2020, Vienna, Austria, September 21-23, 2020, Proceedings
- PowerShell for business intelligence and big data analytics : LiveLessons
- Practical DMX queries for Microsoft SQL Server Analysis Services 2008
- Practical Data Science with R, Second Edition
- Practical DataOps : delivering agile data science at scale
- Practical Python Data Wrangling and Data Quality : Getting Started with Reading, Cleaning, and Analyzing Data
- Practical Synthetic Data Generation
- Practical applications of data mining
- Practical data analysis with JMP
- Practical data mining
- Practical data science cookbook : practical recipes on data pre-processing, analysis and visualization using R and Python
- Practical data science with R
- Practical data science with R : video edition
- Practical data wrangling : expert techniques for transforming your raw data into a valuable source for analytics
- Practical machine learning for data analysis using python
- Practical real-time data processing and analytics : distributed computing and event processing using Apache Spark, Flink, Storm, and Kafka
- Practical recommender systems
- Practical text mining and statistical analysis for non-structured text data applications
- Practical web scraping for data science : best practices and examples with Python
- Praxiseinstieg Machine Learning mit Scikit-Learn und TensorFlow : Konzepte, Tools und Techniken für intelligente Systeme
- Predictive Data Mining Models
- Predictive analytics for dummies
- Predictive analytics with Excel LiveLessons : (sneak peek video training)
- Predictive data mining models
- Predictive modeling with SAS Enterprise Miner : practical solutions for business applications
- Predictive modeling with SAS Enterprise Miner : practical solutions for business applications, second edition
- Present tense : the challenges and trade-offs in building a web-scale real-time analytics system
- Principles of data mining
- Principles of data science
- Principles of data science : a beginner's guide to statistical techniques and theory to build effective data-driven applications
- Principles of data wrangling : practical techniques for data preparation
- Pro Salesforce analytics cloud : a guide to Wave Platform, Builder, and Explorer
- Process mining in action : principles, use cases and outlook
- Process-Mining : Geschäftsprozesse: Smart, Schnell und Einfach
- Processing Covid-19 data with Apache Spark
- Project management analytics : a data-driven approach to making rational and effective project decisions
- Python 3 and data analytics : pocket primer
- Python 3 für Studium und Ausbildung : Einfach lernen und professionell anwenden
- Python Data Analysis : Perform Data Collection, Data Processing, Wrangling, Visualization, and Model Building Using Python
- Python Data Cleaning Cookbook : Modern Techniques and Python Tools to Detect and Remove Dirty Data and Extract Key Insights
- Python companion to data science : collect - organize - explore - predict - value
- Python data analytics : data analysis and science using Pandas, Matplotlib and the Python programming language
- Python data science handbook : essential tools for working with data
- Python for Probability, Statistics, and Machine Learning
- Python for R users : a data science approach
- Python for data analysis
- Python for data analysis : data wrangling with Pandas, NumPy, and IPython
- Python for data analysis : step-by-step with projects
- Python for data science
- Python for data science for dummies
- Python for secret agents : gather, analyze, and decode data to reveal hidden facts using Python, the perfect tool for all aspiring secret agents
- Python vs. R for data science
- Python w analizie danych : Przetwarzanie danych za pomoca ̜pakietów Pandas i NumPy oraz środowiska IPython
- Qlik sense : advanced data visualization for your organization : learning path : create smart data visualizations and predictive analytics solutions
- R : mining spatial, text, web, and social media data : create and customize data mioning algorithms : a course in three modules
- R : predictive analysis : master the art of predictive modeling
- R data mining : implement data mining techniques through practical use cases and real-world datasets
- R deep learning projects : master the techniques to design and develop neural network models in R
- R web scraping quick start guide : techniques and tools to crawl and scrape data from websites
- Reactive Python for data science : push-based data analysis with RxPy
- Real time analytics at Uber : bring SQL into everything
- Real user measurements : why the last mile is the relevant mile
- Real world active learning : applications and strategies for human-in-the-loop machine learning
- Real-time analytics : techniques to analyze and visualize streaming data
- Real-time big data analytics : design, process, and analyze large sets of complex data in real time
- Real-time big data analytics : emerging architecture
- Real-time fraud detection analytics on IBM System Z
- Real-time searching of big data with Solr and Hadoop
- Real-world data mining : applied business analytics and decision making
- Real-world examples of business data use
- Rebuilding reliable data pipelines through modern tools
- Relational data clustering : models, algorithms, and applications
- Reporting, predictive analytics, and everything in between : a guide to selecting the right analytics for you
- Reproducible Data Science with Pachyderm : Learn How to Build Version-Controlled, End-to-end Data Pipelines Using Pachyderm 2. 0
- Research and Development in Knowledge Discovery and Data Mining : Second Pacific-Asia Conference, PAKDD-98 Melbourne, Australia, April 15-17, 1998 Proceedings
- Retail : lessons learned from the first data-driven business and future directions
- SAS Data Integration Studio 4.9 : user's guide
- SAS Viya : the Python perspective
- SEO mit Google Search Console : Webseiten mit kostenlossen Tools optimieren
- SQL for data analysis : perform fast and efficient data analysis with the power of SQL
- Sampling techniques for supervised or unsupervised tasks
- Scala and Spark for big data analytics : tame big data with Scala and Apache Spark!
- Scala data analysis cookbook : navigate the world of data analysis, visualization, and machine learning with over 100 hands-on Scala recipes
- Scala for data science : leverage the power of Scala to build scalable, robust data science applications
- Scala programming for big data analytics : get started with big data analytics using Apache Spark
- Scala programming for big data analytics : get started with big data analytics using Apache Spark
- Scalable machine learning : complex data analysis at scale
- Security in IoT social networks
- Segmentation and lifetime value models using SAS
- Semi-supervised and unsupervised machine learning : novel strategies
- Service-oriented distributed knowledge discovery
- Shadow algorithms data miner
- Shang zhan shu ju wa jue : ni xu yao le jie de shu ju ke xue yu fen xi si wei = Data science for business
- She qun wang zhan de zi liao tan kan
- Shu ju qu dong li : qi ye shu ju fen xi shi zhan = Creating a data-driven organization
- Similarity Search and Applications : 13th International Conference, SISAP 2020, Copenhagen, Denmark, September 30 - October 2, 2020, Proceedings
- Simulation for data science with R : harness actionable insights from your data with computational statistics and simulations using R
- Smart Data Discovery Using SAS Viya
- Smart Geography : 100 Years of the Bulgarian Geographical Society
- Social CRM : market research
- Social Computing with Artificial Intelligence
- Social Network Analysis for Startups : Finding connections on the social web
- Social big data mining
- Social media analytics : techniques and insights for extracting business value out of social media
- Social media data mining and analytics
- Spark : the definitive guide : big data processing made simple
- Spark for data science : analyze your data and delve deep into the world of machine learning with the latest Spark version, 2.0
- Spatio-Temporal Databases : The CHOROCHRONOS Approach
- Spectral feature selection for data mining
- Speech and Computer : 22nd International Conference, SPECOM 2020, St. Petersburg, Russia, October 7-9, 2020, Proceedings
- Speeding from data to insight in financial services : best practices for getting actionable insight from data early and often
- Splunk 7 essentials : demystify machine data by leveraging datasets, building reports, and sharing powerful insights
- Splunk 7.x quick start guide : gain business data insights from operational intelligence
- Splunk : enterprise operational intelligence delivered : demystify big data and discover how to bring operational intelligence to your data to revolutionize your work
- Splunk best practices : design, implement, and publish custom Splunk applications by following best practices
- Splunk developer's guide : learn the a to z of building excellent Splunk applications with the latest techniques using this comprehensive guide
- Splunk essentials : a fast-paced and practical guide to demystifying big data and transforming it into operational intelligence
- Splunk for beginners : make the most of machine data using Splunk
- Splunk operational intelligence cookbook : over 70 practical recipes to gain operational data intelligence with Splunk Enterprise
- Splunk operational intelligence cookbook : over 80 recipes for transforming your data into business-critical insights using Splunk