Incoming Resources
- Learn data mining through Excel, a step-by-step approach for understanding machine learning methods, Hong Zhou
- Technofeudalism, What Killed Capitalism., Yanis Varoufakis
- Predictive analytics for the modern enterprise, by Nooruddin Abbas Ali
- Web scraping with Python, data extraction from the modern web, Ryan Mitchell
- Python for data science for dummies, by John Paul Mueller and Luca Massaron
- Confident data skills, how to work with data and futureproof your career, Kirill Eremenko
- Mastering the SAS DS2 procedure, advanced data wrangling techniques, Mark Jordan
- Marketing data science, modeling techniques in predictive analytics with R and Python, Thomas W. Miller
- Data Smart, Using Data Science to Transform Information into Insight /, Jordan Goldmeier
- Splunk 7 essentials, demystify machine data by leveraging datasets, building reports, and sharing powerful insights, J-P Contreras, Erickson Delgado, Betsy Page Sigman
- Big data, principles and best practices of scalable real-time data systems, Nathan Marz, with James Warren
- Reactive Python for data science, push-based data analysis with RxPy, with Thomas Nield
- Simulation for data science with R, harness actionable insights from your data with computational statistics and simulations using R, Matthias Templ
- Pandas cookbook, recipes for scientific computing, time series analysis and data visualization using Python, Theodore Petrou
- IBM Watson Content Analytics, discovering actionable insight from your content, Wei-Dong (Jackie) Zhu [and others]
- Mastering Splunk, optimize your machine-generated data effectively by developing advanced analytics with Splunk, James Miller
- Pentaho data integration, beginner's guide : get up and running with the Pentaho Data Integration tool using this hands-on, easy-to-read guide, María Carina Roldán
- R web scraping quick start guide, techniques and tools to crawl and scrape data from websites, Olgun Aydin
- Practical data science with Python 3, synthesizing actionable insights from data, Ervin Varga
- Making predictions with data and Python, Alvaro Fuentes
- Network science with Python, explore the networks around us using network science, social network analysis, and machine learning, David Knickerbocker
- Big data analytics, turning big data into big money, Frank J. Ohlhorst
- The security data lake, leveraging big data technologies to build a common data repository for security, Raffael Marty
- Applied data mining for business analytics, Dursun Delen
- Mastering Kibana 6.x, visualize your Elastic Stack data with histograms, maps, charts, and graphs, Anurag Srivastava
- Data Analysis in the Cloud, Models, Techniques and Applications, Domenico Talia, Paolo Trunfio, Fabrizio Marozzo
- Democratizing Business Analytics (Audio Book), Lorica, Ben
- Implementing Splunk, a comprehensive guide to help you transform big data into valuable business insights with Splunk 6.2, Vincent Bumgarner, James D. Miller
- Data science from scratch, first principles with Python, Joel Grus
- Mastering Spark for structured streaming, building end-to-end structured streaming applications with Spark 2.0, Michael Li, The Data Incubator
- Analyzing big data with Hadoop, AWS, and EMR, understanding how to use Hadoop on Amazon's Elastic MapReduce Service, with Frank Kane
- Leveraging multi-CDN at Riot Games, Ray Panahon, Kristopher Beevers
- Not all data is created equal, balancing risk and reward in a data-driven economy, Gregory Fell and Mike Barlow
- Building cognitive applications with IBM Watson services, Alfio Gliozzo [and eleven others], Volume 1
- Learning Apache Apex, Real-time streaming applications with Apex, Thomas Weise, Munagala V. Ramanath, David Yan, Kenneth Knowles
- Hands-on with Amazon Redshift, large scale data warehouse design in the cloud, with Rich Morrow
- Beginning data analysis with Python and Jupyter, use powerful industry-standard tools to unlock new, actionable insight from your existing data, by Alex Galea
- Become a Python data analyst, perform exploratory data analysis and gain insight into scientific computing using Python, Alvaro Fuentes
- Python vs. R for data science, Michael Grogan
- Real-time big data analytics, emerging architecture, Mike Barlow
- Predictive modeling with SAS Enterprise Miner, practical solutions for business applications, Kattamuri S. Sarma
- Business Intelligence Roadmap, The Complete Project Lifecycle for Decision-Support Applications
- Kibana essentials, use the functionalities of Kibana to reveal insights from the data and build attractive visualizations and dashboards for real-world scenarios, Yuvraj Gupta
- The culture of big data, Mike Barlow
- Pandas shu ju qing xi yu jian mo
- Spark programming in Scala for beginners with Apache Spark 3
- How can I clean my data for use in a predictive model?, Matthew North
- Data mining, theories, algorithms, and examples, Nong Ye
- Head first data analysis, Michael Milton
- Data science from scratch, first principles with Python, Joel Grus